{"meta":{"exportedAt":"2026-11-02T06:15:33.471Z","formatVersion":2,"selection":{"q":"pregnancy","system":"","harm":"","context":"","country":"","role":"","relation":"","evidence":"","year":"","response":"","severity":"","verification":"","view":"incidents","sort":"added"},"totalIncidents":3,"coverage":{"cases":3,"countries":3,"languages":1,"unknownLocation":0,"locationPending":0,"unknownLanguage":0,"unknownDate":0,"lawsuits":0,"regulatory":0,"minors":0,"coreRelations":1,"contextualRelations":2,"mixedRelations":0,"unknownRelations":0,"relationPending":0,"relationUnknown":0},"countingNote":"Distinct public cases in this selection. People counts apply within individual cases only; cross-case person overlap has not been resolved. No population incidence estimate.","affectedCountNote":"Interpret person counts with affectedCountStatus and the reported effects. Unquantified zeros are placeholders, not a measured zero.","source":"AI incidents","publisher":"NOPE","url":"https://nope.net/incidents","license":"CC BY 4.0"},"incidents":[{"id":"2025-india-pregnant-women-and-new-mothers-report-poshan-tracker-face-match-failures-cut-off-take-home-rations","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"Starting July 1, 2025, the Union Ministry of Women and Child Development (MoWCD) has officially made facial recognition system (FRS) mandatory for pregnant and lactating women to access take-home rations (THR) under the scheme POSHAN Abhiyaan, sparking concerns over potential exclusions and operational hurdles.; The government has updated the POSHAN Tracker mobile application to make sure the order is implemented, removing the previously available option to ‘skip’ the step for facial recognition.","relation":"supports","source_id":"s4"}],"assertion":"From 1 July 2025 India's Ministry of Women and Child Development made the facial recognition system mandatory for pregnant and lactating women to receive take-home rations, and the Poshan Tracker app was updated to remove the option to skip the facial recognition step.","causal_attribution":"Down To Earth's report of the ministry's order and the app update."},{"id":"c2","status":"reported","evidence":[{"locator":"Across India, pregnant women and nursing mothers are being denied emergency food rations because facial recognition technology fails to match their current appearance to years-old identity photographs, a Decode investigation has found.","relation":"supports","source_id":"s1"},{"locator":"The app attempts to match her current appearance with that reference image in real time, using the Facial Recognition Technology (FRT).","relation":"supports","source_id":"s2"}],"assertion":"The app's facial recognition compares the beneficiary's live face with a stored reference photograph (her Aadhaar photograph), and Decode reports that it fails to match women whose faces have changed since that photograph.","causal_attribution":"Decode's description of the system in two reports; the matching method is not disclosed by the government."},{"id":"c3","status":"reported","evidence":[{"locator":"was cut off from supplementary nutrition because the facial recognition software could not match her face to a photograph taken eight years earlier; \"I don't look like my Aadhaar photo anymore,\"; \"And the phone linked to my Aadhaar is with my husband. He works at a construction site in Delhi. I cannot receive the one-time password they send.\"","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that a mother in Jharkhand was cut off from supplementary nutrition ten weeks after giving birth because the facial recognition software could not match her face to a photograph taken eight years earlier; she also said she could not receive the one-time password because the phone linked to her Aadhaar was with her husband.","causal_attribution":"Decode's report and the mother's own words; Decode changed her name."},{"id":"c4","status":"reported","evidence":[{"locator":"She had been denied food rations for four months because the AI system could not match her current appearance to an Aadhaar photograph taken before her marriage, when she was noticeably younger.; Her doctor at the local primary health centre had warned her about the risks of poor nutrition late in pregnancy, especially because she was anaemic.; Without the ICDS take-home ration, her diet was largely limited to rice and seasonal vegetables. Milk, eggs and pulses were too expensive.","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that a pregnant woman in Bihar, whom her doctor had warned about poor nutrition because she was anaemic, was denied food rations for four months because the system could not match her current appearance to an older Aadhaar photograph, and that without the ration her diet was largely rice and seasonal vegetables.","causal_attribution":"Decode's report of the woman's account; Decode changed her name."},{"id":"c5","status":"reported","evidence":[{"locator":"gave birth to a healthy baby in December. She has been recovering steadily, but her name remains missing from the welfare system. As a nursing mother, she is entitled to supplementary nutrition, yet she has been unable to access it.","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that the Bihar woman later gave birth to a healthy baby and was recovering, but her name remained missing from the welfare system and as a nursing mother she had not been able to obtain supplementary nutrition.","causal_attribution":"Decode's follow-up; recorded as context, including the healthy birth."},{"id":"c6","status":"reported","evidence":[{"locator":"three pregnant women and five nursing mothers have been removed because their faces no longer match old Aadhaar photos.","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that at one Bihar Anganwadi centre three pregnant women and five nursing mothers were removed because their faces no longer matched old Aadhaar photographs.","causal_attribution":"Decode's account of the centre, from its worker."},{"id":"c7","status":"reported","evidence":[{"locator":"For children who do not yet have Aadhaar numbers, the system uses a parent's identity, usually the mother's. When verification fails, a child is dropped from the rolls.; was instructed to remove at least four children after repeated facial recognition failures linked to their mothers' records.","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that for children aged three to six without Aadhaar numbers the system uses a parent's, usually the mother's, identity, that a child is dropped from the rolls when that verification fails, and that a Jharkhand worker was instructed to remove at least four children after repeated facial recognition failures linked to their mothers' records.","causal_attribution":"Decode's report of the rule and of the worker's account."},{"id":"c8","status":"reported","evidence":[{"locator":"Eight months pregnant and returning for the third consecutive day, she stared into the lens of an aging Android phone, hoping the app would finally recognise her face and allow her to collect the nutrition packet she desperately needed.; Her face had changed with dark spots and tiredness. The app just wouldn’t recognise her,” she said with a tired laugh. “I went to her home after work three times. The FRT failed each time. In the end, I just gave her the food and made a manual entry, hoping my supervisor understands.”","relation":"supports","source_id":"s2"}],"assertion":"In Delhi in July 2025 Decode reported a woman eight months pregnant returning to an Anganwadi centre for a third consecutive day hoping the app would recognise her face, and a worker who said the app would not recognise a new mother whose face had changed after three home visits, so she gave her the food and made a manual entry.","causal_attribution":"Decode's reporting and the worker's account."},{"id":"c9","status":"reported","evidence":[{"locator":"The faces and bodies of pregnant and lactating mothers change frequently, so they no longer match the images captured during the registration. The app doesn’t account for these changes, and as a result, some mothers are forced to leave without receiving their rations,","relation":"supports","source_id":"s3"}],"assertion":"The general secretary of the Karnataka Anganwadi workers' union told The South First that pregnant and lactating mothers' faces change so they no longer match the images captured at registration, and that as a result some mothers are forced to leave without their rations.","causal_attribution":"The union leader's statement to The South First."},{"id":"c10","status":"reported","evidence":[{"locator":"Government figures show that of 4.73 crore eligible beneficiaries, 4.51 crore (over 91%) had completed initial documentation and were awaiting face matching as of 31 December 2025. Yet only 2.79 crore (52.7%) had successfully received rations through facial recognition. Nearly half had been locked out.; The Ministry of Women and Child Development did not respond to Decode’s questions about where the missing beneficiaries are, how many have been permanently removed from welfare rolls, or what evidence exists that the system has prevented fraud.","relation":"supports","source_id":"s1"}],"assertion":"Government figures cited by Decode show that of 4.73 crore eligible beneficiaries, 4.51 crore had completed initial documentation and 2.79 crore (52.7%) had received rations through facial recognition as of 31 December 2025; the Ministry did not answer Decode's questions about the missing beneficiaries.","causal_attribution":"Decode's reading of government data; the figures do not separate face-match failures from other causes."},{"id":"c11","status":"reported","evidence":[{"locator":"Before the AI can scan a face, the women must first complete Aadhaar electronic verification, requiring updated Aadhaar details and access to a mobile number linked to the ID to receive a one-time password. This process is called Aadhaar eKYC. For many women, this is where the process breaks down. Mobile numbers are often outdated, inactive, or tied to phones that travel with husbands to distant worksites. Without the password, verification stalls and the beneficiary drops out before reaching the facial recognition stage.","relation":"supports","source_id":"s1"},{"locator":"Mandatory facial recognition under such conditions risks excluding the very people the scheme is meant to serve. This is compounded by slow network speeds, failed facial scans and frequent server crashes.","relation":"supports","source_id":"s4"}],"assertion":"Decode reports that many women drop out earlier, at Aadhaar eKYC, because they cannot receive a one-time password on the mobile number linked to their Aadhaar; Down To Earth reports slow networks, failed scans and server crashes.","causal_attribution":"Recorded as counterevidence: some exclusions come from steps other than the face match."},{"id":"c12","status":"reported","evidence":[{"locator":"said a review of the app’s installation file (APK) shows that it includes components of Google ML Kit used for face detection.; Responding to Decode’s query, Google said that ML Kit “does not have facial recognition capabilities” and is not designed to identify specific individuals.; the government has not disclosed who built the facial verification system, whether it was tested for accuracy on the populations it now excludes, or what safeguards exist when the comparison fails.","relation":"supports","source_id":"s1"}],"assertion":"A researcher who analysed the Poshan Tracker app for Decode found Google's ML Kit face-detection library in it; Google told Decode that ML Kit does not have facial recognition capabilities, and Decode reports that the government has not disclosed who built the facial verification system.","causal_attribution":"The researcher's analysis and Google's statement as reported by Decode."},{"id":"c13","status":"reported","evidence":[{"locator":"On February 11, an app update introduced a limited alternative identity provision, applicable only to pregnant and lactating women. The update allows workers to upload documents such as voter ID cards, bank passbooks, passports, or ration cards. However, this change allows a woman’s name to be added to the system only after the Anganwadi supervisor verifies and approves the alternate identity document.; The workaround still requires facial recognition, leaving the fundamental problem unresolved.","relation":"supports","source_id":"s1"}],"assertion":"Decode reports that on 11 February 2026 an app update allowed workers to upload other identity documents for pregnant and lactating women, adding a woman only after an Anganwadi supervisor approves the document, while registration through a father's or guardian's Aadhaar still requires eKYC and face capture.","causal_attribution":"Decode's account of the government's partial change."}],"effects":[{"label":"pregnant woman reported to have gone four months without take-home rations after the face match failed","claim_id":"c4","direction":"negative"},{"label":"eight women reported removed from one centre's ration rolls after failed face matches","claim_id":"c6","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.decodeinternet.in/decode/ai-facial-recognition-is-denying-food-to-pregnant-women-across-india-30878","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-11-02 (decodeinternet.in, BOOM's Decode desk); no translation.","independence_group":"decode-2026-03-investigation"},{"id":"s2","url":"https://www.decodeinternet.in/decode/when-a-face-scan-decides-who-eats-and-who-keeps-their-job-29048","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-11-02; no translation.","independence_group":"decode-2025-07-delhi"},{"id":"s3","url":"https://thesouthfirst.com/news/in-karnataka-anganwadis-facial-recognition-tech-is-disrupting-ration-delivery-to-pregnant-women-mothers/","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-11-02; no translation.","independence_group":"south-first-2025-08"},{"id":"s4","url":"https://www.downtoearth.org.in/food/mandatory-facial-recognition-for-womens-nutrition-scheme-sparks-fears-of-exclusion-and-tech-failures","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-11-02; no translation.","independence_group":"down-to-earth-2025-07"}],"version":1,"ai_roles":["institutional_use"],"contexts":["public_services","health"],"unknowns":["Who built the face-matching component and its accuracy on pregnant and nursing women; no test results are published.","How many beneficiaries were refused or removed because of face-match failures as distinct from eKYC, one-time-password or connectivity failures.","Whether the women described later regained their rations, or whether rations missed were restored.","Whether any court has ruled on the challenges to mandatory facial recognition; none is reported in the inspected sources."],"geography":{"basis":"Decode reports from Anganwadi centres in Bihar, Jharkhand and Delhi and The South First from Karnataka, all under India's ICDS scheme.","court_countries":[],"event_countries":["IN"],"affected_person_countries":["IN"]},"publication":{"basis":"Published as a government welfare app's mandatory face match that, according to Decode's reporting from named states, did not recognise pregnant women and new mothers against old identity photographs, so that described women were refused or removed from take-home rations and children were dropped. The accounts are attributed; Google's statement, the government figures and the non-face-match causes are recorded.","reviewed_on":"2026-11-02"},"ai_involvement":{"basis":"Decode, The South First and Down To Earth describe a mandatory facial recognition step in the Poshan Tracker app that compares a woman's live face with her Aadhaar or registration photograph before the app releases her take-home ration. Decode reports specific women whom this automated check did not recognise, and who were refused rations or removed from the rolls as a result, and workers say they cannot hand over rations when the app does not show a name. The non-match of a genuine beneficiary is the recognition system's own output. The government has not disclosed the matching component; a researcher found Google ML Kit face detection in the app, and Google says ML Kit does not recognise individuals. No analysis of individual failures is reported, and some exclusions arise at earlier one-time-password steps, which are kept separate.","status":"reported"},"person_relations":["made_decision_about"]},"name":"India: pregnant women and new mothers report being cut off from take-home rations when the Poshan Tracker app's face match failed","summary":"From 1 July 2025 India's Ministry of Women and Child Development made a facial recognition check in the government's Poshan Tracker app mandatory before pregnant women and nursing mothers receive take-home rations under the Integrated Child Development Services (ICDS) scheme; the app compares the woman's live face with her Aadhaar identity photograph. In July 2025 Decode reported from Delhi that a woman eight months pregnant returned to her Anganwadi centre for a third day trying to get the app to recognise her, and a worker said she gave food to a new mother the app would not recognise and recorded it by hand. In August 2025 the Karnataka Anganwadi workers' union told The South First that the faces of pregnant and nursing mothers change so they no longer match their registration images, and that some mothers leave without their rations. In March 2026 a Decode investigation supported by the Pulitzer Center reported that a mother in Jharkhand was cut off from supplementary nutrition ten weeks after giving birth because the software could not match her face to a photograph taken eight years earlier, that a pregnant woman in Bihar who was anaemic went four months without rations because the system could not match her to an older Aadhaar photograph, that one Bihar centre had removed three pregnant women and five nursing mothers whose faces no longer matched, and that a Jharkhand worker was told to remove at least four children whose eligibility depended on their mothers' failed face matches. Decode also reports failures earlier in the process, when women cannot receive a one-time password on an Aadhaar-linked phone. Government figures cited by Decode show 52.7% of eligible beneficiaries had received rations through facial recognition by 31 December 2025. A researcher who analysed the app for Decode found Google's ML Kit face-detection library in it; Google said ML Kit cannot recognise individuals, and the government has not disclosed who built the matching system. After workers' protests, a February 2026 app update let workers upload other identity documents for pregnant and nursing women, subject to a supervisor's approval. Decode reports the Bihar woman later gave birth to a healthy baby, while her name remained missing from the system.","incidentDate":"2025-07-01","incidentKind":"ongoing_experience","incidentDatePrecision":"month","exposurePattern":"repeated_interactions","reportedDate":"2025-07-17","aiSystem":"Facial recognition (FRS) in the Government of India's Poshan Tracker app, which matches a beneficiary's live face with her Aadhaar photograph before take-home rations are released; the matching component is undisclosed, and a researcher found Google ML Kit face detection in the app","aiProduct":"Poshan Tracker face recognition","severity":"medium","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["other_material_harm","psychological_distress"],"harmOutcomeSummary":"Decode reports that women whose faces the app did not match against old Aadhaar photographs were refused or removed from supplementary food rations, including an anaemic pregnant woman who went four months without them and a mother cut off ten weeks after giving birth, and that children were dropped when their mothers' matches failed; workers and a union leader describe mothers leaving without rations and frustration at repeated failed scans.","frameworkFacets":[],"causationStatus":"alleged","participantUsersAffectedMin":0,"otherPeopleHarmedMin":9,"affectedCountStatus":"partial","affectedCountEvidence":"Decode reports one Bihar centre where three pregnant women and five nursing mothers were removed because their faces no longer matched old Aadhaar photographs, and a Jharkhand mother cut off when the software could not match her face (9). The anaemic Bihar woman may be among that centre's eight and is not added. Other figures (nearly 10 women at another centre, at least four children, nationwide shares) are approximate, overlap, or are not tied to the face match alone, so they are not counted.","victimAgeRange":"adult","jurisdiction":"IN","platformType":"other","outcomeType":"internal_action","outcomeStatus":"ongoing","primarySourceUrl":"https://www.decodeinternet.in/decode/ai-facial-recognition-is-denying-food-to-pregnant-women-across-india-30878","primarySourceLabel":"Decode, AI Facial Recognition Is Denying Food To Pregnant Women Across India, 19 March 2026","firstPublishedAt":"2026-11-02T03:08:56.021165+00:00","updatedAt":"2026-11-02T03:08:56.021165+00:00","scopeVersion":"facts-v3","tags":["facial-recognition","public-services","take-home-rations","pregnancy","welfare","india"]},{"id":"2026-oxfordshire-gp-practice-patients-say-ai-phone-triage-could-not-help-or-misread-call-reason","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"'began using the AI Andi triage system in July, with all calls made to the surgery passing through the bot'; 'All calls to the surgery go through the AI system, which can then pass them onto a human receptionist'","relation":"supports","source_id":"s1"},{"locator":"'began using the AI Andi triage system in July, with all calls made to the surgery passing through the bot'","relation":"supports","source_id":"s2"}],"assertion":"Newbury Street Practice in Wantage began using the AI Andi triage system in July 2026, and all calls to the surgery pass through it; the system can pass calls on to a human receptionist.","causal_attribution":"Practice arrangement as reported by the LDRS; not disputed by the practice."},{"id":"c2","status":"reported","evidence":[{"locator":"'She said she had been waiting in a phone queue for 20 minutes, after which \"he decided he couldn't help me\".'; 'the AI bot \"puts you off ever bothering\" contacting the practice'","relation":"supports","source_id":"s1"},{"locator":"'She said she had been waiting in a phone queue for 20 minutes, after which \"he decided he couldn't help me\".'","relation":"supports","source_id":"s2"}],"assertion":"One patient says she waited in the phone queue for 20 minutes, after which the AI system decided it could not help her, and that the system is a wall that puts patients off contacting the practice.","causal_attribution":"Patient's own account to the reporter; the system's reasons and the date of the call are not reported."},{"id":"c3","status":"reported","evidence":[{"locator":"'who said she was left \"frustrated\" after the AI system thought she was \"calling about pregnancy\"'","relation":"supports","source_id":"s1"},{"locator":"'who said she was left \"frustrated\" after the AI system thought she was \"calling about pregnancy\"'","relation":"supports","source_id":"s2"}],"assertion":"Another patient says she was left frustrated after the AI system took her call to be about pregnancy.","causal_attribution":"Patient's own account; the system's classification is known only from her description."},{"id":"c4","status":"reported","evidence":[{"locator":"'it was now giving patients the option to speak to a human receptionist instead of AI'; 'feedback on the AI tool had been \"79% positive\"'; 'particularly those less confident with technology, have found the change harder'","relation":"supports","source_id":"s1"},{"locator":"'feedback on the AI tool had been \"79% positive\"'","relation":"supports","source_id":"s2"}],"assertion":"A practice spokesperson said most feedback had been positive (79% in the first month), that some patients less confident with technology had found the change harder, and that patients are now offered the option to speak to a human receptionist.","causal_attribution":"Practice statement; the basis of the 79% figure is not described."},{"id":"c5","status":"reported","evidence":[{"locator":"'Local MP Olly Glover recently contributed to the debate, after being contacted by residents in his Didcot and Wantage constituency.'","relation":"supports","source_id":"s1"}],"assertion":"The local MP said residents had contacted him about the system and that he had been in touch with the practice.","causal_attribution":"MP's statement as reported; the number of residents is not given."}],"effects":[{"label":"patients left waiting without help or misdirected by the AI phone triage system, describing frustration and a barrier to care (patients' accounts)","claim_id":"c2","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.bbc.co.uk/news/articles/cmglwe2kel7no","kind":"news_report","access":"read","language":"en","translation_note":"Read in English by the research agent (an AI) on 2026-10-17 (HTTP 200); no translation. Written by the Local Democracy Reporting Service and published by BBC News on 14 October 2026 (updated 15 October).","independence_group":"ldrs-wantage-gp-ai-receptionist"},{"id":"s2","url":"https://www.yahoo.com/news/world/articles/patients-frustration-gp-surgerys-ai-144053050.html","kind":"news_report","access":"read","language":"en","translation_note":"Read in English by the research agent (an AI) on 2026-10-17 (HTTP 200); no translation. Yahoo News syndication of the same BBC/LDRS article, so it shares the original's source group and adds no independent support.","independence_group":"ldrs-wantage-gp-ai-receptionist"}],"version":1,"ai_roles":["institutional_use"],"contexts":["health","public_services"],"unknowns":["The dates of the two patients' calls and whether either later reached a clinician.","How many other patients had similar experiences; the practice reports no complaint count.","Why the system could not help the first patient and how it classified the second patient's call.","When the option to speak to a human receptionist was introduced."],"geography":{"basis":"The report places the practice in Wantage, Oxfordshire, England, and the calls were made to that practice by its patients.","court_countries":[],"event_countries":["GB"],"affected_person_countries":["GB"]},"publication":{"basis":"Published as patients' attributed accounts, reported by the Local Democracy Reporting Service, of an AI phone triage system's own responses (declining to help after a 20-minute wait, misreading a call as about pregnancy) and the frustration and access barrier they describe. The practice's statement that most feedback was positive and its change to offer a human receptionist are recorded.","reviewed_on":"2026-10-17"},"ai_involvement":{"basis":"The practice confirms that all calls pass through the AI Andi triage system. The patients describe the system's own responses to them: after a 20-minute queue it decided it could not help one patient, and it took another patient's call to be about pregnancy. The patients connect these responses to their frustration and to the system acting as a wall to care. Whether either patient later reached a clinician, and the system's internal reasons, are not reported.","status":"reported"},"person_relations":["communicated_with"]},"name":"Oxfordshire GP practice patients say its AI phone triage left them without help or misread why they called; practice reports mostly positive feedback","summary":"Newbury Street Practice, a GP surgery in Wantage, Oxfordshire, began routing every incoming call through the AI Andi triage system in July 2026. In a Local Democracy Reporting Service article published by BBC News on 14 October 2026, one patient says she waited in the phone queue for 20 minutes before the AI system decided it could not help her, and described the system as a wall that puts patients off contacting the practice. Another patient says she was left frustrated when the system took her call to be about pregnancy. A practice spokesperson said most feedback had been positive (79% in the first month), that some patients less confident with technology had found the change harder, and that patients are now offered the option of speaking to a human receptionist. The local MP said residents had contacted him about the system.","incidentDate":"2026-07-01","incidentEndDate":"2026-10-14","incidentKind":"bounded_series","incidentDatePrecision":"range","exposurePattern":"single_interaction","reportedDate":"2026-10-14","aiSystem":"AI Andi, an AI telephone triage and receptionist system through which all calls to Newbury Street Practice, Wantage, pass and which can hand calls on to a human receptionist","aiProduct":"AI Andi","severity":"low","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["psychological_distress"],"harmOutcomeSummary":"Two patients say the practice's AI phone triage system left one waiting 20 minutes before deciding it could not help and misread the other's reason for calling, leaving them frustrated and describing it as a barrier to care (patients' accounts; the practice reports mostly positive feedback).","frameworkFacets":[],"causationStatus":"alleged","participantUsersAffectedMin":2,"otherPeopleHarmedMin":0,"affectedCountStatus":"partial","affectedCountEvidence":"Two patients counted: the one who waited 20 minutes before the system decided it could not help, and the one whose call the system took to be about pregnancy; both dealt with the system directly. The report says other patients raised concerns and the practice says some patients found the change harder, but gives no number; a third patient's opinion about cost-cutting is not counted as harm.","victimAgeRange":"unknown","platformType":"other","outcomeStatus":"pending","primarySourceUrl":"https://www.bbc.co.uk/news/articles/cmglwe2kel7no","primarySourceLabel":"BBC News (Local Democracy Reporting Service), 14 Oct 2026: patients frustrated by Wantage GP surgery's AI receptionist","firstPublishedAt":"2026-10-17T03:07:47.328581+00:00","updatedAt":"2026-10-17T03:07:47.328581+00:00","scopeVersion":"facts-v3","tags":["gp-practice","phone-triage","ai-receptionist","healthcare-access","nhs"]},{"id":"2026-us-meta-26-employees-sue-alleging-ai-assisted-may-layoff-selection-penalized-protected-leave","caseFacts":{"claims":[{"id":"c1","status":"documented","evidence":[{"locator":"OAKLAND DIVISION","relation":"supports","source_id":"s1"},{"locator":"Filed 07/13/26","relation":"supports","source_id":"s1"},{"locator":"Plaintiffs initiated this lawsuit on July 13, 2026, bringing claims against Meta","relation":"supports","source_id":"s2"},{"locator":"A group of 26 Meta employees has sued the company, claiming it used artificial intelligence systems to select people for layoffs, disproportionately targeting those on medical, parental or family leave.","relation":"supports","source_id":"s6"}],"assertion":"On 13 July 2026 twenty-six anonymous plaintiffs (Does 1 through 26) filed a complaint against Meta Platforms, Inc. in the US District Court for the Northern District of California, Oakland division, alleging employment discrimination in the May 2026 reduction in force.","causal_attribution":"The filing of the complaint is documented by the court record. The complaint establishes only the plaintiffs’ allegations."},{"id":"c2","status":"reported","evidence":[{"locator":"activity-monitoring data, AI-token-usage dashboards, and algorithmically assisted","relation":"supports","source_id":"s1"},{"locator":"artificial-intelligence-assisted systems to score, rank, and select employees for inclusion","relation":"supports","source_id":"s1"},{"locator":"algorithmic productivity scoring drawn from keystroke, screen-content, mouse,","relation":"supports","source_id":"s1"},{"locator":"The parties dispute whether Meta utilized AI in deciding to terminate plaintiffs’","relation":"supports","source_id":"s2"},{"locator":"They claim that Meta used a number of internal AI-assisted systems to score and rank employees on a termination list.","relation":"supports","source_id":"s7"}],"assertion":"The complaint alleges, on information and belief, that Meta used a set of internal AI-assisted systems to score, rank and select employees for the termination list: the Metamate internal large-language-model assistant, employee-trained \"second brain\" agents, keystroke and other activity-monitoring data, AI-token-usage dashboards, and algorithmically assisted performance ranking and calibration.","causal_attribution":"These are the plaintiffs’ allegations, pleaded on information and belief and supported by plaintiff declarations that were not inspected (they are quoted in the complaint and the order). Meta disputes them (claim c4). The news reports and the court order restate the complaint and are one reporting chain with it."},{"id":"c3","status":"reported","evidence":[{"locator":"be accumulated by an employee who is on protected medical or family leave, or whose","relation":"supports","source_id":"s1"},{"locator":"protected-leave-takers or accommodation-seekers for individualized human review. Meta","relation":"supports","source_id":"s1"},{"locator":"On information and belief, Meta did not neutralize any of the foregoing inputs for","relation":"supports","source_id":"s1"},{"locator":"result was that employees who took protected leaves were disproportionately selected for","relation":"supports","source_id":"s1"},{"locator":"Plaintiffs are twenty-six current and former Meta employees, each of whom Meta","relation":"supports","source_id":"s1"},{"locator":"selected for separation in the RIF, and each of whom","relation":"supports","source_id":"s1"},{"locator":"About half the plaintiffs had taken leave for caregiving or pregnancy-related reasons.","relation":"supports","source_id":"s6"}],"assertion":"The complaint alleges that the inputs to these systems cannot be accumulated by an employee on protected medical, family or parental leave, that Meta did not neutralise them for protected leave, and that employees who took protected leave were therefore disproportionately selected for layoff. It states that each plaintiff was selected for separation in the reduction in force and had, within the 24 months before it, taken, requested or been approved for protected leave, or requested or received a disability accommodation.","causal_attribution":"Allegation of the plaintiffs. The court found on 17 July 2026 only serious questions going to the merits and no likelihood of success on that record (claim c5). Whether any AI system affected any plaintiff’s selection is unresolved."},{"id":"c4","status":"reported","evidence":[{"locator":"Workforce management and organizational decisions were and are made by people, not AI.","relation":"supports","source_id":"s6"},{"locator":"selection decisions in the RIF were “made by human","relation":"supports","source_id":"s2"},{"locator":"promotion history over a defined period. There was no AI-","relation":"supports","source_id":"s2"},{"locator":"was selected based on leave status, disability, or any other protected characteristic,","relation":"supports","source_id":"s2"},{"locator":"“selection decision [was] made by ‘AI.’” Id. ¶ 11.","relation":"supports","source_id":"s2"},{"locator":"Selection decisions were made by human business leaders","relation":"supports","source_id":"s9"},{"locator":"defined period. There was no AI-assisted “scoring” or “ranking” related to employee","relation":"supports","source_id":"s9"},{"locator":"guidance does not permit AI adoption and usage metrics to be used as negative factors in","relation":"supports","source_id":"s3"},{"locator":"performance reviews in 2025 or as selection criteria in the RIF.","relation":"supports","source_id":"s3"}],"assertion":"Meta denies the allegations. A Meta spokesperson said workforce management and organisational decisions were made by people, not AI. In declarations filed by a Meta human-resources director, Meta states that selection decisions were made by human business leaders using documented neutral criteria, that no AI-assisted scoring or ranking of employee performance was used, that no plaintiff was selected on the basis of leave status or disability, and that no selection decision was made by AI.","causal_attribution":"Meta’s statements and declarations about its own process. They are a party account and had been tested only through briefing and court hearings (claims c5 and c7), not in discovery."},{"id":"c5","status":"documented","evidence":[{"locator":"described below, the TRO is DENIED.","relation":"supports","source_id":"s2"},{"locator":"The parties dispute whether Meta utilized AI in deciding to terminate plaintiffs’","relation":"supports","source_id":"s2"},{"locator":"plaintiffs have not shown a likelihood of success on the merits, but rather a “serious question[]”","relation":"supports","source_id":"s2"},{"locator":"Loss of health care, employment, protected leave, and unvested restricted stock units (“RSUs”) are","relation":"supports","source_id":"s2"},{"locator":"Loss of immigration status is different. Four of the plaintiffs have employment-based,","relation":"supports","source_id":"s2"},{"locator":"they were not in the rooms where it happened.","relation":"supports","source_id":"s2"}],"assertion":"On 17 July 2026 the court denied the plaintiffs’ motion for a temporary restraining order. The order records that the parties dispute whether Meta used AI in deciding to terminate the plaintiffs, finds serious questions going to the merits but no shown likelihood of success on that record, finds that loss of health care, employment, protected leave and unvested equity can be remedied in arbitration, and treats the possible loss of immigration status for four plaintiffs with Meta-sponsored visas as a potentially irreparable harm that needed more information.","causal_attribution":"A court order establishes what the court ruled and recorded. It does not establish that AI was or was not used in the selection."},{"id":"c6","status":"reported","evidence":[{"locator":"On May 20, 2026, Meta began notifying the selected employees by email, beginning with","relation":"supports","source_id":"s1"},{"locator":"finalized on or about July 22, 2026 (and on or about August 20, 2026 for New York","relation":"supports","source_id":"s1"},{"locator":"laid off on May 20, 2026.” Complaint (“Compl.”) [Dkt. No. 1] ¶ 45 (the “mass reduction in force”","relation":"supports","source_id":"s2"},{"locator":"Though they have been notified of their layoffs, all 26 remain employed by Meta, with separations set to begin July 22.","relation":"supports","source_id":"s6"},{"locator":"Meta in May notified nearly 8,000 employees, or about 10% of its global workforce, that they were losing their jobs","relation":"supports","source_id":"s7"},{"locator":"Laid-off workers remain on the payroll but lost access to Meta systems on May 20","relation":"supports","source_id":"s7"}],"assertion":"Meta began notifying employees selected in the reduction in force on 20 May 2026 (about 8,000 employees, roughly 10 percent of its workforce). The complaint says the plaintiffs were notified of their selection from that date, and that separations were scheduled for about 22 July 2026 (later for some plaintiffs). Meta said in court filings that laid-off workers stayed on the payroll but lost access to Meta systems on 20 May.","causal_attribution":"The notification date and the scheduled separation dates come from the complaint and Meta court filings as relayed by Reuters. The sources inspected do not report whether each separation took place on its scheduled date, although Courthouse News called the plaintiffs former employees on 24 August 2026."},{"id":"c7","status":"reported","evidence":[{"locator":"Hearing on Motion for Preliminary Injunction conducted via videoconference. The Court","relation":"supports","source_id":"s5"},{"locator":"summarizes tentative. Argument of counsel heard. Motion taken under submission; written order","relation":"supports","source_id":"s5"},{"locator":"I have a record I have to deal with and the record at the moment does not persuade me of the merits","relation":"supports","source_id":"s8"},{"locator":"categorical denial of any impact of AI in the termination process","relation":"supports","source_id":"s8"},{"locator":"whether what plaintiffs think happened, happened","relation":"supports","source_id":"s8"}],"assertion":"The court held a hearing on the plaintiffs’ preliminary injunction motion on 24 August 2026, heard argument and took the motion under submission with a written order to follow. Courthouse News reports that the judge said the record at that time did not persuade the judge of the merits, that the plaintiffs’ evidence raised some potential questions about Meta’s categorical denial of any impact of AI in the termination process, and that the case turns on whether what plaintiffs think happened, happened.","causal_attribution":"The minute entry documents that the hearing occurred and the motion was taken under submission. The judge’s remarks are reported by one news outlet and the transcript was not inspected. No written ruling on the preliminary injunction was found as of 29 September 2026."},{"id":"c8","status":"documented","evidence":[{"locator":"and only Plaintiff Doe 20, hereby voluntarily dismisses","relation":"supports","source_id":"s10"},{"locator":"remain parties and continue to prosecute this action","relation":"supports","source_id":"s10"},{"locator":"Doe 20 was voluntarily dismissed from this action on August 3, 2026 pursuant to Federal","relation":"supports","source_id":"s4"},{"locator":"is made on behalf of Doe 20, and no relief is sought on Doe 20’s behalf.","relation":"supports","source_id":"s4"}],"assertion":"One plaintiff (Doe 20) voluntarily dismissed all of that plaintiff’s claims without prejudice on 3 August 2026 (Dkt. 33), and the notice states that Does 1 through 19 and 21 through 26 remain parties. No reason is given in the notice.","causal_attribution":"A filing by the plaintiffs’ counsel records the dismissal. It does not say whether that plaintiff was selected in the reduction in force or why the dismissal was made."},{"id":"c9","status":"reported","evidence":[{"locator":"They recognize that their claims must be arbitrated, and they have initiated arbitration proceedings","relation":"supports","source_id":"s2"},{"locator":"with the American Arbitration Association (AAA). Here, they seek a temporary restraining order:","relation":"supports","source_id":"s2"},{"locator":"while they pursue their claims in private arbitration","relation":"supports","source_id":"s7"},{"locator":"from this Court only the status-quo-preserving provisional relief that Meta’s own","relation":"supports","source_id":"s1"},{"locator":"G. Reserve to the arbitral forum all relief on the merits, including but not limited to","relation":"supports","source_id":"s1"}],"assertion":"The 17 July 2026 order records that the plaintiffs recognize their claims must be arbitrated and that they have initiated arbitration proceedings with the American Arbitration Association. The complaint says the plaintiffs seek from the court only status-quo-preserving provisional relief pending an independent audit of the selection process and arbitration of the merits, and it reserves merits relief such as reinstatement, back pay and damages to the arbitral forum.","causal_attribution":"The order records the plaintiffs’ own statement about their arbitration filings. The arbitration itself is confidential and its progress is unknown."}],"effects":[{"label":"Employees on or after protected leave allegedly disproportionately selected for layoff by an AI-assisted process that did not account for leave (disputed by Meta)","claim_id":"c3","direction":"negative"},{"label":"Plaintiffs notified of selection for termination on 20 May 2026, with separations scheduled from 22 July 2026 and possible loss of health coverage, unvested equity and (for four plaintiffs) work-visa status","claim_id":"c6","direction":"negative"}],"sources":[{"id":"s1","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.1.0.pdf","kind":"court_filing","access":"read","language":"en","translation_note":"","independence_group":"meta-complaint"},{"id":"s2","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.25.0.pdf","kind":"court_order","access":"read","language":"en","translation_note":"","independence_group":"ndcal-court-record"},{"id":"s3","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.42.1_1.pdf","kind":"court_filing","access":"read","language":"en","translation_note":"","independence_group":"meta-court-declarations"},{"id":"s4","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.46.0.pdf","kind":"court_filing","access":"read","language":"en","translation_note":"","independence_group":"ndcal-court-record"},{"id":"s5","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.49.0.pdf","kind":"court_record","access":"read","language":"en","translation_note":"","independence_group":"ndcal-court-record"},{"id":"s6","url":"https://www.cbsnews.com/news/26-meta-workers-sue-ai-aided-layoffs-medical-family-leave/","kind":"wire_report","access":"read","language":"en","translation_note":"","independence_group":"meta-complaint"},{"id":"s7","url":"https://www.spokesman.com/stories/2026/jul/17/us-judge-wont-block-meta-from-laying-off-workers-w/","kind":"wire_report","access":"read","language":"en","translation_note":"","independence_group":"reuters-tro-coverage"},{"id":"s8","url":"https://www.courthousenews.com/meta-workers-claiming-ai-fired-them-unlikely-to-see-relief/","kind":"news_report","access":"read","language":"en","translation_note":"","independence_group":"courthouse-news-hearing"},{"id":"s9","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.31.0.pdf","kind":"court_filing","access":"read","language":"en","translation_note":"","independence_group":"meta-court-declarations"},{"id":"s10","url":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.33.0.pdf","kind":"court_filing","access":"read","language":"en","translation_note":"","independence_group":"ndcal-court-record"}],"version":1,"ai_roles":["institutional_use"],"contexts":["work","health"],"unknowns":["Whether any AI system scored, ranked or selected any plaintiff is unresolved. The complaint pleads it on information and belief. Meta denies it in declarations. No discovery had occurred in the sources inspected, and the judge said on 17 July 2026 that plaintiffs were not in the rooms where the selections happened.","The sources inspected do not show how many people beyond the plaintiffs were selected because of leave, or how many of the roughly 8,000 laid-off employees were scored by any AI-assisted system. Only the plaintiffs are counted as reported harmed.","The order on the preliminary injunction motion (argued 24 August 2026, taken under submission) had not been found by 29 September 2026. The hearing remarks were read only through one news report and the transcript was not inspected.","Whether each plaintiff’s separation took place on its scheduled date (22 July 2026 for most, later for some) is not stated in the sources inspected. Reuters and CBS/AP describe the plaintiffs as still employed in July, and Courthouse News called them former employees on 24 August 2026.","One plaintiff (Doe 20) was voluntarily dismissed on 3 August 2026 and no reason is stated. The affected count therefore uses 25.","The complaint and declarations contain individual medical, pregnancy and immigration details. They are anonymised in the public copies and are deliberately not described here.","Reuters and WSJ pages for the initial filing could not be read (HTTP 401). Reuters coverage of the 17 July ruling was read through a Spokesman-Review copy. The Law.com article was behind a subscription wall and was not cited.","The complaint alleges that data captured by a separate Meta employee-monitoring program (the Model Capability Initiative) supplied inputs to the selection process, and Meta denies that AI was used in the selection. That program’s own privacy and security consequences are a different event, recorded as 2026-meta-mci-us-employee-keystroke-and-screen-capture-for-ai-training-then-internal-data-exposure, and are not part of this record."],"geography":{"basis":"The complaint states that the plaintiffs worked in California, Illinois, Washington, New York, the District of Columbia, Pennsylvania and Florida and the suit is in the US District Court for the Northern District of California. Meta also notified employees in other countries in the same reduction in force, but no plaintiff outside the US is described.","court_countries":["US"],"event_countries":["US"],"affected_person_countries":["US"]},"publication":{"basis":"The complaint, the court order denying the temporary restraining order, two Meta declarations, the plaintiffs’ notice of dismissal of one plaintiff and the hearing minute entry were read from the court record (CourtListener copies), with CBS/AP, Reuters and Courthouse News reports. Every AI-related statement is attributed. The plaintiffs are anonymous in the record and are not described individually. Meta denies that AI made or informed any selection decision and the court has not resolved the dispute.","reviewed_on":"2026-09-29"},"ai_involvement":{"basis":"The complaint alleges, on information and belief, that Meta used internal AI-assisted systems (Metamate, second-brain agents, activity-monitoring scoring, AI-token-usage dashboards, algorithmic ranking and calibration) to score, rank and select employees for the 20 May 2026 termination list. Meta’s declarations say selection decisions were made by human business leaders and that there was no AI-assisted scoring or ranking related to employee performance, and the court described the declarations as saying Meta did not use AI in any way with respect to the RIF. The court recorded that the parties dispute whether Meta used AI in deciding to terminate the plaintiffs and found on 17 July 2026 that the plaintiffs had not shown a likelihood of success on the current record. On 24 August 2026 the judge said the plaintiffs’ evidence raised some potential questions about Meta’s categorical denial. No discovery had tested Meta’s account in the sources inspected.","status":"disputed"},"person_relations":["made_decision_about","made_claim_about"]},"name":"US: 26 Meta employees sue alleging an AI-assisted May 2026 layoff selection penalized workers on protected leave, Meta says people made the decisions","summary":"On 20 May 2026 Meta began notifying about 8,000 employees (roughly 10 percent of its workforce) that they had been selected for layoff. On 13 July 2026 twenty-six anonymous employees who had taken or requested medical, pregnancy, parental or family leave, or a disability accommodation, sued Meta in the US District Court for the Northern District of California. The complaint alleges, on information and belief, that Meta used internal AI-assisted systems (including the Metamate assistant, keystroke and activity monitoring, AI-token-usage dashboards and algorithmic performance ranking) to score, rank and select employees, and that these inputs could not accumulate during protected leave, so plaintiffs on leave were disproportionately selected. Meta says workforce decisions were made by people, not AI, and that no selection decision was made by AI. On 17 July 2026 the court denied a temporary restraining order, recording that the parties dispute whether Meta used AI in the terminations and finding serious questions on the merits but no shown likelihood of success. One plaintiff was voluntarily dismissed on 3 August 2026. The preliminary injunction motion was argued on 24 August 2026 and taken under submission. The plaintiffs are pursuing their merits claims in arbitration and the allegations are unproven.","incidentDate":"2026-05-20","incidentKind":"single_event","incidentDatePrecision":"day","exposurePattern":"unknown","reportedDate":"2026-07-14","aiSystem":"Meta internal AI-assisted systems alleged in the complaint: the Metamate internal LLM assistant, employee-trained \"second brain\" agents, keystroke and activity-monitoring productivity scoring, AI-token-usage dashboards and AI-assisted performance calibration (Meta denies AI was used in selecting employees for the layoff)","aiProduct":"Meta internal AI systems (reported)","aiCompany":"Meta Platforms, Inc.","severity":"medium","verificationStatus":"disputed","harmCategories":[],"harmOutcomes":["professional_harm"],"harmOutcomeSummary":"The complaint alleges that 26 employees were selected for termination in Meta’s May 2026 reduction in force through an AI-assisted process that penalised protected leave, with separations scheduled from 22 July 2026 and asserted losses of employer-subsidised health coverage, unvested equity and, for four plaintiffs, work-visa status. Meta denies that AI was used in the selections. The court found the alleged harms other than immigration status remediable in arbitration and has not decided the merits.","frameworkFacets":[],"causationStatus":"disputed","participantUsersAffectedMin":0,"otherPeopleHarmedMin":25,"affectedCountStatus":"documented_minimum","affectedCountEvidence":"The complaint states that each of 26 plaintiffs was selected for separation in the May 2026 reduction in force. One plaintiff was voluntarily dismissed on 3 August 2026 without a stated reason, so 25 active plaintiffs are counted as a documented minimum. The roughly 8,000 other employees notified in the reduction in force are not counted because no source ties their selection to the alleged AI process.","victimAgeRange":"adult","platformType":"other","primarySourceUrl":"https://storage.courtlistener.com/recap/gov.uscourts.cand.474171/gov.uscourts.cand.474171.1.0.pdf","primarySourceLabel":"Complaint, Does 1 through 26 v. Meta Platforms, Inc. (N.D. Cal., filed 13 Jul 2026)","firstPublishedAt":"2026-09-29T21:16:06.345461+00:00","updatedAt":"2026-09-30T01:17:57.733761+00:00","scopeVersion":"facts-v3","tags":["historical-2026"]}]}