{ "id": "AIBD-0120", "title": "ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna; human operators verify it and Cal Fire holds the fire to under a quarter acre", "summary": "AI on Cleveland National Forest cameras flagged smoke at about 3 am on 5 August 2023; Cal Fire held the verified fire under a quarter acre.", "date_observed": "2023-08-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At about 3 am on 5 August 2023, the ALERTCalifornia AI flagged a column of smoke in the Cleveland National Forest near Mount Laguna. That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers.", "category": "protective response", "unexpected": false, "purpose": "The tool was built to spot smoke in ALERTCalifornia camera feeds and notify Cal Fire emergency command centers. Crews can then reach a fire in its incipient phase. This detection was that purpose.", "system": "ALERTCalifornia AI wildfire detection (machine-learned smoke and anomaly detection on the ALERTCalifornia pan-tilt-zoom camera network)", "model_version": null, "developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path", "deployer": "California Department of Forestry and Fire Protection (CAL FIRE)", "location": "Mount Laguna, California, United States", "domain": "Emergency services (wildfire detection and response)", "segment": "State fire agency using a university camera network", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-09-12-f6ac" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Cal Fire's Mount Laguna station received a verified alert at about 3 am. Its crews extinguished the fire at under a quarter acre. Cal Fire intelligence specialist Suzann Leininger says the system “is getting us time to react in a faster manner”." }, { "group": "societal", "depth": 2, "reason": "Residents, property and forest around Mount Laguna were spared a larger fire. Captain Yeary's statement that it “could have been a devastating fire” is a judgment, not a proven counterfactual." } ], "ai_role": { "status": "assessed", "statement": "The model's contribution was the detection. Its algorithm flagged a smoke column in a Cleveland National Forest camera feed at about 3 am. Human operators verified it before Cal Fire was alerted. The containment was done by Captain Yeary's crews. No source records whether a 911 call would have come later. The time gained is documented only for the program as a whole. TIME reports 77 fires identified before any 911 call in the first two months. UC San Diego's Neal Driscoll says the alerts beat 911 calls about 40 percent of the time. AFP also notes the system sometimes misreads dust, insects or weather as smoke. That is why the human verification step sits between the model and the dispatch." }, "evidence": [ { "kind": "news report", "citation": "Fonsegrives R. / AFP via Phys.org (2023). California firefighters use AI to battle wildfires. AFP wire report.", "title": "California firefighters use AI to battle wildfires", "url": "https://phys.org/news/2023-09-california-firefighters-ai-wildfires.html", "date": "2023-09-12", "written_by": "independent", "quote": "Had the AI not alerted us to it, it could have gotten much bigger" }, { "kind": "news report", "citation": "AFP via Asharq Al-Awsat English (2023). California Firefighters Use AI to Battle Wildfires. Same AFP wire text (not independent of the Phys.org copy).", "title": "California Firefighters Use AI to Battle Wildfires", "url": "https://english.aawsat.com/node/4540976", "date": "2023-09-12", "written_by": "independent", "quote": "Human operators were able to verify the machines were correct and alerted Yeary" }, { "kind": "news report", "citation": "AFP via France 24 (2023). California firefighters use AI to battle wildfires. Same AFP wire text (not independent).", "title": "California firefighters use AI to battle wildfires", "url": "https://www.france24.com/en/live-news/20230912-california-firefighters-use-ai-to-battle-wildfires", "date": "2023-09-12", "written_by": "independent", "quote": "We beat 911 calls about 40 percent of the time. And it's going to get better." }, { "kind": "news report", "citation": "Fonsegrives R. / AFP via Oman Observer (2023). Firefighters use AI to battle wildfires. Same AFP wire text (not independent).", "title": "Firefighters use AI to battle wildfires", "url": "https://www.omanobserver.om/article/1142729/opinion/firefighters-use-ai-to-battle-wildfires", "date": "2023-09-12", "written_by": "independent", "quote": "It's getting us time to react in a faster manner." }, { "kind": "press release", "citation": "CAL FIRE and ALERTCalifornia (2023). CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial. Agency press release, Sacramento.", "title": "CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial", "url": "https://alertcalifornia.org/cal-fire-and-university-of-california-san-diegos-alertcalifornia-program-join-forces-to-enhance-wildfire-response-with-artificial-intelligence-implementation-trial/", "date": "2023-07-10", "written_by": "makers", "quote": "a machine-learned model has been created to accurately differentiate between smoke and other particles in the air" }, { "kind": "news report", "citation": "Dixit P. / TIME (2023). AlertCalifornia and Cal Fire AI Wildfire Detector. The Best Inventions of 2023.", "title": "AlertCalifornia and Cal Fire AI Wildfire Detector", "url": "https://time.com/collection/best-inventions-2023/6327137/alertcalifornia-ai-wildfire-detector/", "date": "2023-10-24", "written_by": "independent", "quote": "In the first two months, the system had correctly identified 77 fires before any 911 calls came in." }, { "kind": "press release", "citation": "Scully C. / UC San Diego Today (2023). ALERTCalifornia and CAL FIRE's Fire Detection AI Program Named One of TIME's Best Inventions of 2023. University news release.", "title": "ALERTCalifornia and CAL FIRE's Fire Detection AI Program Named One of TIME's Best Inventions of 2023", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "date": "2023-10-24", "written_by": "makers", "quote": "The AI tool became available to all 21 CAL FIRE 911 Dispatch Centers in September 2023." }, { "kind": "news report", "citation": "Jennewein C. / Times of San Diego (2023). Time Magazine: California's AI Wildfire Detection System a Top Invention of 2023. Describes a second AI-first detection near Grass Valley on 11 September 2023.", "title": "Time Magazine: California's AI Wildfire Detection System a Top Invention of 2023", "url": "https://timesofsandiego.com/tech/2023/10/24/time-magazine-californias-ai-wildfire-detection-system-a-top-invention-of-2023/", "date": "2023-10-24", "written_by": "independent", "quote": "the first 911 call was not made until 6:01 a.m., and firefighters were already at the scene" }, { "kind": "press release", "citation": "ALERTCalifornia / UC San Diego (n.d.). Technology. Programme web page describing the AI detection workflow and watchstander vetting.", "title": "ALERTCalifornia: Technology", "url": "https://alertcalifornia.org/technology/", "date": null, "written_by": "makers", "quote": "If the incident is vetted and confirmed by trained watchstanders, firefighters respond quickly to extinguish the fire at the incipient phase." } ], "replication": { "produced_by": [ "A camera network with machine-learned smoke detection watching remote forest at night, when human spotting is weakest", "A verification step by trained operators that turns a model flag into a confirmed alert to the local Cal Fire station", "A fire still small at detection, with a crew close enough to reach it before it grows" ], "must_hold": [ "The detection must precede any human report for the time gained to be attributable to the model. For this fire no source documents the absence of a 911 call", "Human verification must be fast enough that the alert still arrives in the incipient phase", "False positives from dust, insects or weather must be screened out so that crews keep trusting the alerts" ], "echoes": [] }, "paired_incident": null, "headline": "ALERTCalifornia AI flags smoke; fire held under a quarter acre", "metric": "Cal Fire held the verified fire under a quarter acre", "comparator": { "against": "911 calls from the public as the first notice of a fire", "before": "not stated", "after": "the AI beats 911 calls about 40 percent of the time", "basis": "measured", "quote": "\"We beat 911 calls about 40 percent of the time. And it's going to get better.\"", "url": "https://english.aawsat.com/node/4540976" }, "later": { "status": "scaled", "date": "2023-09-01", "note": "After the summer trial the AI tool was rolled out to all 21 Cal Fire dispatch centers in September 2023 (day not given; first day of month used), and TIME named it one of the best inventions of 2023 on 24 October 2023.", "quote": "The AI tool became available to all 21 Cal Fire dispatch centers in September. The new tool is especially effective in spotting anomalies in remote locations and has proven effective at night, even alerting firefighters before 911 calls.", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-09-12-f6ac", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://english.aawsat.com/node/4540976; https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://alertcalifornia.org/about/; https://en.wikipedia.org/wiki/California_Department_of_Forestry_and_Fire_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0120", "catalog_version": "1.0.0", "source_fingerprint": "6a95bb51aedb168ccf10e609ab16860e9bcb15daf5287425833fc7fb98bb145b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0120-source-0001", "AIBD-0120-source-0002", "AIBD-0120-source-0003", "AIBD-0120-source-0004", "AIBD-0120-source-0005", "AIBD-0120-source-0006", "AIBD-0120-source-0007", "AIBD-0120-source-0008", "AIBD-0120-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path", "deployer": "California Department of Forestry and Fire Protection (CAL FIRE)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model's contribution was the detection. Its algorithm flagged a smoke column in a Cleveland National Forest camera feed at about 3 am. Human operators verified it before Cal Fire was alerted. The containment was done by Captain Yeary's crews. No source records whether a 911 call would have come later. The time gained is documented only for the program as a whole. TIME reports 77 fires identified before any 911 call in the first two months. UC San Diego's Neal Driscoll says the alerts beat 911 calls about 40 percent of the time. AFP also notes the system sometimes misreads dust, insects or weather as smoke. That is why the human verification step sits between the model and the dispatch." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "ALERTCalifornia flagged smoke in a camera feed at about 3 a.m. Operators verified the detection and notified Cal Fire, whose crews contained the fire.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The model's contribution was the detection. Its algorithm flagged a smoke column in a Cleveland National Forest camera feed at about 3 am. Human operators verified it before Cal Fire was alerted. The containment was done by Captain Yeary's crews. No source records whether a 911 call would have come later. The time gained is documented only for the program as a whole. TIME reports 77 fires identified before any 911 call in the first two months. UC San Diego's Neal Driscoll says the alerts beat 911 calls about 40 percent of the time. AFP also notes the system sometimes misreads dust, insects or weather as smoke. That is why the human verification step sits between the model and the dispatch." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Cal Fire's Mount Laguna station received a verified alert at about 3 am. Its crews extinguished the fire at under a quarter acre. 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under a quarter acre", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The account does not establish when a 911 call would otherwise have arrived. 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The new tool is especially effective in spotting anomalies in remote locations and has proven effective at night, even alerting firefighters before 911 calls.", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Operators checked the alert before dispatch because dust, insects, and weather can produce false detections. 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That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALERTCalifornia AI wildfire detection (machine-learned smoke and anomaly detection on the ALERTCalifornia pan-tilt-zoom camera network)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna; human operators verify it and Cal Fire holds the fire to under a quarter acre", "headline": "ALERTCalifornia AI flags smoke; fire held under a quarter acre" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6a95bb51aedb168ccf10e609ab16860e9bcb15daf5287425833fc7fb98bb145b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 3 am on 5 August 2023, the ALERTCalifornia AI flagged a column of smoke in the Cleveland National Forest near Mount Laguna. That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers.", "replication": { "produced_by": [ "A camera network with machine-learned smoke detection watching remote forest at night, when human spotting is weakest", "A verification step by trained operators that turns a model flag into a confirmed alert to the local Cal Fire station", "A fire still small at detection, with a crew close enough to reach it before it grows" ], "must_hold": [ "The detection must precede any human report for the time gained to be attributable to the model. For this fire no source documents the absence of a 911 call", "Human verification must be fast enough that the alert still arrives in the incipient phase", "False positives from dust, insects or weather must be screened out so that crews keep trusting the alerts" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }