{ "id": "AIBD-0355", "title": "India's YES-TECH AI/ML yield estimates settle PMFBY crop-insurance claims, perhaps faster; Madhya Pradesh gives them 100% weight", "summary": "Launched 21 July 2023; nine states by Jan 2025; Madhya Pradesh 100% weightage from kharif 2023. PIB claims faster claims; CSE and DTE report lower payouts and rollback calls in three districts.", "date_observed": "2023-07-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested.", "system": "YES-TECH (Yield Estimation System based on Technology): satellite remote sensing, weather data and analytical models, including an 'AI/ML model' for kharif crops and a 'semi-physical model' for rabi crops in Madhya Pradesh", "model_version": null, "developer": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)", "deployer": "Government of Madhya Pradesh under PMFBY with insurers (AIC, SBI General Insurance, HDFC Ergo); nine states in all as of January 2025", "location": "Madhya Pradesh, India (CSE field assessment in Sehore, Vidisha and Bhopal districts)", "domain": "Agricultural crop insurance / yield estimation", "segment": "Government crop-insurance scheme (PMFBY)", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "Officials claim faster claim settlement without figures, while independent sources report lower payouts and rollback demands in three districts.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No verified individual outcome. CSE reports some farmers valuing faster disbursement and others reporting lower claims than losses." }, { "group": "organizational", "depth": null, "reason": "PIB claims faster settlement without figures. CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "depth": null, "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ], "ai_role": { "status": "assessed", "statement": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. No independent quantified beneficial outcome was found." }, "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ], "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "date": null, "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "model_version": null, "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] }, "paired_incident": null, "headline": "YES-TECH may speed PMFBY crop-insurance claims", "metric": "kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore", "comparator": { "against": "claims paid under manual crop-cutting experiments (2018)", "before": "R217.91 crore", "after": "R55.2 crore", "basis": "measured", "quote": "For instance, between 2018 and 2024, claim amounts disbursed in Bhopal, Sehore and Vidisha districts dropped from a total of R217.91 crore to R55.2 crore in the kharif season; and from R110.5 crore to just R9.28 crore in the rabi season.", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens" }, "later": { "status": "scaled", "date": "2025-01-01", "note": "By January 2025 nine states had adopted YES-TECH with Madhya Pradesh fully transitioned, per the PIB backgrounder of 14 February 2026; Down To Earth reports that Madhya Pradesh farmers and unions protested low payouts in 2024-25.", "quote": "As of January 2025, it has been adopted by nine states, with Madhya Pradesh fully transitioning to technology-based yield estimation, thereby enabling timely loss assessment and faster claim settlement.", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "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://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "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" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, two independent news reports and three press releases from the makers. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0355", "catalog_version": "1.0.0", "source_fingerprint": "8ab6dfa1e286704fc3aa3f673427f6be6cc4553446cd4c78058ac6bca2ace34b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0355-source-0001", "AIBD-0355-source-0002", "AIBD-0355-source-0003", "AIBD-0355-source-0004", "AIBD-0355-source-0005", "AIBD-0355-source-0006", "AIBD-0355-source-0007", "AIBD-0355-source-0008" ], "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": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)", "deployer": "Government of Madhya Pradesh under PMFBY with insurers (AIC, SBI General Insurance, HDFC Ergo); nine states in all as of January 2025" } }, "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": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. No independent quantified beneficial outcome was found." } } }, "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": "YES-TECH produced estimates of crop yields that Madhya Pradesh used to calculate insurance payments. The cited CSE presentation describes an AI or machine-learning model for kharif crops.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. 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CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No verified individual outcome. 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Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore", "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": "Official accounts assert faster settlement without quantified supporting results. CSE and Down To Earth report both appreciation of prompt payments and complaints that the estimates reduced payouts. The sources do not establish an independently measured net benefit.", "editor_note": "" } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2025-01-01", "note": "By January 2025 nine states had adopted YES-TECH with Madhya Pradesh fully transitioned, per the PIB backgrounder of 14 February 2026; Down To Earth reports that Madhya Pradesh farmers and unions protested low payouts in 2024-25.", "quote": "As of January 2025, it has been adopted by nine states, with Madhya Pradesh fully transitioning to technology-based yield estimation, thereby enabling timely loss assessment and faster claim settlement.", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } } }, "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": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0355" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "Officials claim faster claim settlement without figures, while independent sources report lower payouts and rollback demands in three districts." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No verified individual outcome. CSE reports some farmers valuing faster disbursement and others reporting lower claims than losses." }, { "group": "organizational", "reason": "PIB claims faster settlement without figures. CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Madhya Pradesh, India (CSE field assessment in Sehore, Vidisha and Bhopal districts)", "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-07-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "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://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "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.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "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://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "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.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Agricultural crop insurance / yield estimation", "segment": "Government crop-insurance scheme (PMFBY)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0355-source-0001", "AIBD-0355-source-0002", "AIBD-0355-source-0003", "AIBD-0355-source-0004", "AIBD-0355-source-0005", "AIBD-0355-source-0006", "AIBD-0355-source-0007", "AIBD-0355-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Launched 21 July 2023; nine states by Jan 2025; Madhya Pradesh 100% weightage from kharif 2023. PIB claims faster claims; CSE and DTE report lower payouts and rollback calls in three districts.", "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources." } }, "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": "YES-TECH (Yield Estimation System based on Technology): satellite remote sensing, weather data and analytical models, including an 'AI/ML model' for kharif crops and a 'semi-physical model' for rabi crops in Madhya Pradesh" } }, "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": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)" } }, "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": "India's YES-TECH AI/ML yield estimates settle PMFBY crop-insurance claims, perhaps faster; Madhya Pradesh gives them 100% weight", "headline": "YES-TECH may speed PMFBY crop-insurance claims" } }, "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": [ "8ab6dfa1e286704fc3aa3f673427f6be6cc4553446cd4c78058ac6bca2ace34b" ], "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": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "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": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }