{"meta":{"exportedAt":"2026-11-07T02:55:39.817Z","formatVersion":2,"selection":{"q":"finance","system":"","harm":"","context":"","country":"","role":"","relation":"contextual","evidence":"","year":"2021","response":"","severity":"","verification":"","view":"incidents","sort":"added"},"totalIncidents":4,"coverage":{"cases":4,"countries":3,"languages":2,"unknownLocation":0,"locationPending":0,"unknownLanguage":0,"unknownDate":0,"lawsuits":1,"regulatory":0,"minors":0,"coreRelations":0,"contextualRelations":4,"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":"2021-brazil-federal-judge-finds-inss-ai-death-record-match-wrongly-ended-living-retirees-pension-awards-damages","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"'O magistrado concluiu que houve falha do sistema de inteligência artificial do INSS ao fazer o cruzamento de dados com o Sistema de Óbitos (Sisobi).'; 'a suspensão do benefício ocorreu automaticamente em 01/05/2021 por comando de inteligência artificial que capturou dados do Sisobi. Os dados utilizados, nome próprio e nome da mãe, não se mostraram suficientes para evitar a indevida cessação do benefício.'","relation":"supports","source_id":"s1"},{"locator":"'a suspensão do benefício ocorreu automaticamente em 01/05/2021 por comando de inteligência artificial que capturou dados do Sisobi'","relation":"supports","source_id":"s2"}],"assertion":"A federal judge concluded that the INSS's artificial intelligence system failed when cross-matching data with the death register (Sisobi), and that the retiree's benefit was suspended automatically on 1 May 2021 by an artificial intelligence command that used only his name and mother's name.","causal_attribution":"The court's finding as the TRF4 news item reports it."},{"id":"c2","status":"reported","evidence":[{"locator":"'sendo prejudicado por não ter qualquer outra fonte de renda'; 'O autor da ação chegou a enviar declaração escrita de próprio punho ao INSS e, embora tenha pessoalmente demonstrado que estava vivo, e não morto, nada foi feito até reativação do benefício em janeiro deste ano (2022).'","relation":"supports","source_id":"s1"}],"assertion":"The retiree said the pension was his only source of income, that he asked for reactivation without a decision, and that he sent a handwritten declaration; the benefit was restored only in January 2022.","causal_attribution":"His account and the court record as the news item gives them."},{"id":"c3","status":"reported","evidence":[{"locator":"'a inteligência artificial adotada pelo INSS se revelou ineficiente ou desinteligente nesta hipótese, de modo que a sua ilegitima inconsistência ocasionou prejuízos materiais à parte autora que atingiram diretamente a sua subsistência, pois se tratava de sua única fonte de rendimentos'; 'o sujeitou a espera de 226 dias'","relation":"supports","source_id":"s1"}],"assertion":"The judge wrote that the INSS's artificial intelligence proved inefficient or unintelligent in this case, that its inconsistency harmed the retiree's subsistence because the pension was his only income, and that the INSS made him wait 226 days.","causal_attribution":"The judge's words quoted in the news item."},{"id":"c4","status":"reported","evidence":[{"locator":"'no valor de R$ 3.917,67 (três mil, novecentos e dezessete reais e sessenta e sete centavos)'; 'os valores atrasados, bem como aqueles vencidos entre a sentença e a efetiva implantação do benefício (DIP) serão executados na forma de requisição de pagamento'","relation":"supports","source_id":"s1"},{"locator":"'no valor de R$ 3.917,67'","relation":"supports","source_id":"s2"}],"assertion":"The judge ordered the INSS to pay R$3,917.67 in moral damages and the arrears.","causal_attribution":"The operative part as reported."}],"effects":[{"label":"pension, his only income, stopped by a wrong automatic death-register match and restored only months later","claim_id":"c3","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.ibdp.org.br/2022/09/30/justica-condena-inss-a-pagar-indenizacao-apos-cancelar-beneficio-de-segurado-que-ainda-estava-vivo/","kind":"news_article","access":"read","language":"pt","translation_note":"Read in Portuguese on 2026-11-02; translation by the research agent, an AI. Professional association's republication of a TRF4 news item ('Fonte TRF4') on the sentence; the sentence was not read.","independence_group":"trf4-news-arapongas-inss-sentence"},{"id":"s2","url":"https://wagner.adv.br/justica-condena-inss-a-pagar-indenizacao-apos-cancelar-beneficio-de-segurado-que-ainda-estava-vivo/","kind":"news_article","access":"read","language":"pt","translation_note":"Read in Portuguese on 2026-11-02; translation by the research agent, an AI. Law firm's republication of the same TRF4 news item ('Fonte: TRF 4ª Região'); undated on the page.","independence_group":"trf4-news-arapongas-inss-sentence"}],"version":1,"ai_roles":["institutional_use"],"contexts":["public_services","finance","justice"],"unknowns":["The case number, the sentence date and whether the INSS appealed.","What kind of system the 'artificial intelligence command' was beyond a name and mother's-name match, and whose death record was matched.","The retiree's age."],"geography":{"basis":"The pension was paid and stopped by Brazil's national social security institute, and a federal court in the 4th federal region of Brazil decided the case.","court_countries":["BR"],"event_countries":["BR"],"affected_person_countries":[]},"publication":{"basis":"Published on a TRF4 court news item, relayed by IBDP and a law firm, reporting a federal judge's finding that an INSS artificial intelligence match with the death register automatically stopped a living retiree's pension, his only income, for months, and the damages awarded.","reviewed_on":"2026-11-02"},"ai_involvement":{"basis":"The federal judge, as the TRF4 news item reports, found that an INSS artificial intelligence command cross-matched the retiree with the death register using only name and mother's name and automatically suspended his pension on 1 May 2021, and that this wrong match caused the loss of his only income. The technical nature of the system beyond the judge's description is not disclosed, and the sentence itself was not read.","status":"supported"},"person_relations":["made_decision_about"]},"name":"Brazilian federal judge finds an INSS AI death-record match wrongly ended a living retiree's pension, his only income, and awards damages","summary":"A Brazilian federal judge in the 4th federal region ordered the social security institute (INSS) to pay a retiree R$3,917.67 in moral damages after finding that his pension had been stopped by a failure of the institute's artificial intelligence system, according to a Federal Regional Court of the 4th Region (TRF4) news item relayed by the Brazilian Institute of Social Security Law on 30 September 2022. The judge explained that the benefit was suspended automatically on 1 May 2021 by an artificial intelligence command that captured data from the death-records system (Sisobi), and that the data used, the person's name and mother's name, were not enough to prevent the wrongful cessation. The retiree said the pension was his only source of income; he asked for reactivation and sent a handwritten declaration, and although he showed in person that he was alive, the benefit was restored only in January 2022. The judge wrote that the AI 'proved inefficient or unintelligent' in this case and that the INSS made him wait 226 days. Arrears were also ordered paid. Whether the INSS appealed is not reported.","incidentDate":"2021-05-01","incidentKind":"single_event","incidentDatePrecision":"day","exposurePattern":"unknown","reportedDate":"2022-09-30","aiSystem":"An INSS artificial intelligence routine that cross-matched benefit records with the national death register (Sisobi) using name and mother's name and stopped benefits automatically","aiProduct":"Unidentified death-record matching system","severity":"medium","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["financial_loss"],"harmOutcomeSummary":"The judge found that an automatic AI match with the death register wrongly stopped the retiree's pension, his only income, and that the INSS took 226 days to restore it, which harmed his subsistence.","frameworkFacets":[],"causationStatus":"established","participantUsersAffectedMin":0,"otherPeopleHarmedMin":1,"affectedCountStatus":"exact","affectedCountEvidence":"One person: the retiree whose pension the automatic match stopped.","victimAgeRange":"unknown","jurisdiction":"BR","platformType":"other","outcomeType":"lawsuit_filed","outcomeStatus":"unknown","primarySourceUrl":"https://www.ibdp.org.br/2022/09/30/justica-condena-inss-a-pagar-indenizacao-apos-cancelar-beneficio-de-segurado-que-ainda-estava-vivo/","primarySourceLabel":"IBDP, Justiça condena INSS a pagar indenização após cancelar benefício de segurado que ainda estava vivo, 30 September 2022","firstPublishedAt":"2026-11-02T03:10:13.026551+00:00","updatedAt":"2026-11-02T03:10:13.026551+00:00","scopeVersion":"facts-v3","tags":["public-benefits","automated-decision","death-register-match","social-security","court-damages"]},{"id":"2021-nevada-unemployment-claimant-says-id-me-face-check-rejected-him-and-locked-him-out-of-benefits","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"which uses a combination of biometric information and official documents to confirm that applicants are who they claim to be.; ID.me CEO Blake Hall told Motherboard that the company’s facial recognition technology does one-to-one matching—comparing one face against a picture of that same face (from a driver’s license, say); At least 21 states use ID.me to detect fraudulent benefit claims.","relation":"supports","source_id":"s1"}],"assertion":"ID.me verifies the identity of people claiming unemployment benefits in at least 21 US states, using biometric information and official documents, including a facial recognition step that compares one face with a picture of that same face, such as from a driving licence.","causal_attribution":"Motherboard's description and ID.me's chief executive's account of the system."},{"id":"c2","status":"reported","evidence":[{"locator":"a gig economy worker in Las Vegas who was suddenly cut off from his unemployment benefits in late March after ID.me failed to identify him.; it rejected it, didn’t give us a reason, just rejected it. It rejected it three times, and then it locked me out of the system.","relation":"supports","source_id":"s1"}],"assertion":"A gig economy worker in Las Vegas says he was suddenly cut off from his unemployment benefits in late March 2021 after ID.me failed to identify him; he says the facial recognition test rejected him three times without giving a reason and then locked him out of the system.","causal_attribution":"The claimant's account to Motherboard; the year comes from the article's date of 18 June 2021."},{"id":"c3","status":"reported","evidence":[{"locator":"He tried contacting the state of Nevada for help, but the employees there directed him back to ID.me.; until he tweeted a scathing criticism of the company, which then reached out and—after several more frustrating days—verified","relation":"supports","source_id":"s1"}],"assertion":"The claimant says ID.me's chat support did not resolve the problem despite many attempts and the state of Nevada directed him back to ID.me; after several weeks he posted a public criticism, and the company contacted him and, after several more days, verified his identity.","causal_attribution":"The claimant's account as reported by Motherboard."},{"id":"c4","status":"reported","evidence":[{"locator":"went for three weeks without receiving his benefit. “I couldn’t pay bills,”","relation":"supports","source_id":"s1"}],"assertion":"The claimant says he went three weeks without his benefit and could not pay bills.","causal_attribution":"The claimant's own statement to Motherboard."},{"id":"c5","status":"reported","evidence":[{"locator":"“The algorithms used for Face Match operate ~99.9% efficacy,” Hall wrote in an email to Motherboard.; Hall said that facial recognition failures are not a problem with the technology but with the people using it to verify their identity.; “We are unaware of eligible individuals who have not been able to verify their identity with ID.me,”","relation":"supports","source_id":"s1"},{"locator":"ID.me chief Blake Hall blamed the problems on users rather than the technology. Face Match algorithms have \"99.9% efficacy,","relation":"supports","source_id":"s2"}],"assertion":"ID.me's chief executive told Motherboard that its Face Match algorithms operate at about 99.9% efficacy, that face-match failures are a problem with the people using the system rather than the technology, and that the company was unaware of eligible individuals unable to verify their identity.","causal_attribution":"ID.me's response, kept as counterevidence; Engadget relays the same statement."},{"id":"c6","status":"reported","evidence":[{"locator":"ID.me unsurprisingly took issue with the Motherboard piece in a response provided to Engadget. Hall called the fraud claims \"inaccurate and defamatory,\" and stressed that the company suck to National Institute of Standards and Technology standards for identification. He reiterated the claims made about the nature of the facial recognition system and the video chat backup","relation":"supports","source_id":"s2"}],"assertion":"In a response to Engadget, ID.me called Motherboard's fraud claims inaccurate and defamatory and repeated its account of the facial recognition system and its video chat backup.","causal_attribution":"ID.me's statement to Engadget."}],"effects":[{"label":"claimant says the face check rejected and locked him out, stopping his benefits for three weeks","claim_id":"c2","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.vice.com/en/article/facial-recognition-failures-are-locking-people-out-of-unemployment-systems/","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-10-30; no translation.","independence_group":"motherboard-2021-06-18"},{"id":"s2","url":"https://www.engadget.com/facial-recognition-failures-id-me-unemployment-benefits-172654494.html","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-10-30; no translation.","independence_group":"engadget-2021-06-19"}],"version":1,"ai_roles":["institutional_use"],"contexts":["public_services","finance"],"unknowns":["The exact dates of the lockout and of the verification; Motherboard gives only late March and three weeks without the benefit.","Why the face match failed in this case: no analysis of the attempts is reported, and ID.me attributes failures in general to users' photos.","Whether the missed benefit weeks were later paid."],"geography":{"basis":"The benefits were Nevada unemployment benefits: the claimant says he sought help from the state of Nevada, which sent him back to ID.me. Motherboard describes him as a gig economy worker in Las Vegas.","court_countries":[],"event_countries":["US"],"affected_person_countries":["US"]},"publication":{"basis":"Published as a state unemployment system's facial recognition identity check rejecting a described claimant three times and locking him out, which he says stopped his benefit for three weeks until the company verified him. His account is attributed; ID.me's explanation that failures come from users is recorded.","reviewed_on":"2026-10-30"},"ai_involvement":{"basis":"Motherboard and ID.me's chief executive describe ID.me Face Match as a facial recognition step that compares a claimant's face with the photo on an identity document. The claimant says that step rejected his face three times and locked him out of the system, which cut off his unemployment benefit, and that ID.me later verified him as the same person after his public complaint. The rejection of a person the company later verified is the system's own failed match. ID.me's chief executive says such failures come from users' photos; the cause in this case is not established.","status":"reported"},"person_relations":["made_decision_about"]},"name":"Nevada unemployment claimant says ID.me face check rejected him three times and locked him out, leaving him three weeks without benefits","summary":"ID.me, an identity-verification company used by at least 21 US states to check people claiming unemployment benefits, asks claimants to pass a facial recognition step that compares their face with a photo of the same person, such as a driving licence. In June 2021 Motherboard (VICE) reported that a gig economy worker in Las Vegas was suddenly cut off from his unemployment benefits in late March after ID.me failed to identify him. He said that when he held his phone in the instructed position the system rejected him three times without giving a reason and then locked him out. He said he tried ID.me's chat support many times and the state of Nevada sent him back to ID.me; after several weeks he posted a public criticism on Twitter, and the company contacted him and, after several more days, verified his identity. He said he went three weeks without his benefit and could not pay bills. ID.me's chief executive told Motherboard that its Face Match algorithms operate at about 99.9% efficacy, that failures are a problem with how people use the system rather than the technology, and that the company was unaware of eligible people unable to verify their identity. Motherboard said other claimants in several states described similar lockouts; those accounts are not counted here.","incidentDate":"2021-03-01","incidentKind":"single_event","incidentDatePrecision":"month","exposurePattern":"repeated_interactions","reportedDate":"2021-06-18","aiSystem":"ID.me Face Match, a one-to-one facial recognition step in ID.me's identity verification for state unemployment benefit claimants, as described by Motherboard and ID.me's chief executive","aiProduct":"ID.me Face Match","aiCompany":"ID.me","severity":"low","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["financial_loss","psychological_distress"],"harmOutcomeSummary":"The claimant says ID.me's face check rejected him three times and locked him out, cutting off his unemployment benefit; he says he went three weeks without it, could not pay bills, and spent weeks trying to reach ID.me and the state before the company verified him. He describes the experience as ridiculous.","frameworkFacets":[],"causationStatus":"alleged","participantUsersAffectedMin":1,"otherPeopleHarmedMin":0,"affectedCountStatus":"exact","affectedCountEvidence":"One claimant describes being rejected by the face check and losing benefits. Motherboard says other claimants in several states complained of similar problems but gives no count tied to the face check, so they are not counted.","victimAgeRange":"adult","jurisdiction":"US","platformType":"other","outcomeType":"media_coverage","outcomeStatus":"resolved","primarySourceUrl":"https://www.vice.com/en/article/facial-recognition-failures-are-locking-people-out-of-unemployment-systems/","primarySourceLabel":"Motherboard (VICE), Facial Recognition Failures Are Locking People Out of Unemployment Systems, 18 June 2021","firstPublishedAt":"2026-10-30T03:05:29.391311+00:00","updatedAt":"2026-10-30T03:05:29.391311+00:00","scopeVersion":"facts-v3","tags":["id-me","facial-recognition","unemployment-benefits","identity-verification","public-services","nevada"]},{"id":"2021-amazon-delivery-drivers-say-netradyne-ai-van-cameras-flagged-driving-events-they-did-not-commit-lowering-bonus-scores","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"'In February, Amazon announced that it would install cameras made by the AI-tech startup Netradyne in its Amazon-branded delivery vans'; 'Each time the camera registers an event, footage is uploaded into a system, recorded, and affects a score drivers receive at the end of the week for safe driving.'","relation":"supports","source_id":"s1"}],"assertion":"Amazon installed AI-powered Netradyne cameras in its delivery vans during 2021; the cameras detect driving events, upload the footage and feed a weekly safe-driving score.","causal_attribution":"Describes the system and its role in the score."},{"id":"c2","status":"reported","evidence":[{"locator":"'the camera in his van started to incorrectly penalize him whenever cars cut him off'; 'the Netradyne camera in his van has also detected “events” that didn’t actually happen, but that impacted his performance score at Amazon'","relation":"supports","source_id":"s1"}],"assertion":"Drivers said the cameras registered events they did not commit or that were not unsafe: a driver in Los Angeles said it incorrectly penalised him when cars cut him off, and a former driver in Texas said it detected events that did not happen and that they affected his performance score.","causal_attribution":"The drivers' accounts attribute the penalties to the camera's detections; Amazon and Netradyne did not address these individual events."},{"id":"c3","status":"reported","evidence":[{"locator":"'A few times, we’ve been in the country on a dirt road, where there’s no stop sign, but the camera flags a stop sign.'; 'If I look into my mirrors to make sure I am safe to change lanes, it dings me for distraction because my face is turned to look into my mirror.'","relation":"supports","source_id":"s1"}],"assertion":"Other drivers described false stop-sign detections, including a stop sign flagged on a dirt road with no sign, and being flagged for distraction when checking mirrors.","causal_attribution":"Drivers' accounts of the cameras' detection errors."},{"id":"c4","status":"reported","evidence":[{"locator":"'For many Amazon drivers, these performance scores determine whether they receive weekly bonuses, prizes, and extra pay.'; 'Before I would be able to win prizes and stuff, as soon as cameras came along, it went downhill,'; 'which receive bonuses by earning “fantastic” scores on a weekly scorecard'","relation":"supports","source_id":"s1"}],"assertion":"According to drivers and an Amazon scorecard document obtained by Motherboard, the weekly scores determine bonuses, prizes and extra pay, and the former Texas driver said winning prizes went downhill once the cameras came.","causal_attribution":"Connects the detections to pay; the amount lost by any individual driver is not reported."},{"id":"c5","status":"reported","evidence":[{"locator":"'but they don’t respond. There’s no room for discussion around the possibility that maybe the camera’s data isn’t clean.'; 'made the appeal process futile.'","relation":"supports","source_id":"s1"}],"assertion":"The Los Angeles driver said requests through his delivery company to see the photos flagged as events went unanswered, and a delivery-company owner said appeals were futile.","causal_attribution":"The drivers' and owner's account of the appeal route."},{"id":"c6","status":"reported","evidence":[{"locator":"'a team of Amazon employees manually reviews all events that are appealed to ensure that erroneous events do not impact drivers or Amazon delivery companies'; 'This technology provides drivers real-time alerts to help them stay safe when they are on the road.'; 'accidents had decreased by 48 percent'","relation":"supports","source_id":"s1"}],"assertion":"Amazon said the cameras give real-time safety alerts, that accidents had fallen 48 percent since installation, and that its employees manually review all appealed events so that erroneous events do not affect drivers.","causal_attribution":"Amazon's response; its safety figures are its own claims."}],"effects":[{"label":"Drivers say false camera events lowered their weekly scores","claim_id":"c2","direction":"negative"},{"label":"Scores decide bonuses and prizes","claim_id":"c4","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.vice.com/en/article/amazons-ai-cameras-are-punishing-drivers-for-mistakes-they-didnt-make/","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-10-27 (HTTP 200, full article body).","independence_group":"motherboard-netradyne-2021-09-20"}],"version":1,"ai_roles":["institutional_use"],"contexts":["work","finance"],"unknowns":["How many events recorded against these drivers were wrong, and whether any was later overturned on appeal.","How much bonus or prize value any individual driver lost.","Whether Amazon or Netradyne changed the detection thresholds after these reports."],"geography":{"basis":"The drivers worked from Amazon delivery stations in Los Angeles, Sugar Land (Texas), Mobile (Alabama), Oklahoma and Kentucky, and the vans and routes are in the United States.","court_countries":[],"event_countries":["US"],"affected_person_countries":["US"]},"publication":{"basis":"Published because the drivers describe specific detection errors by the AI cameras (cars cutting in scored as unsafe following, mirror checks scored as distraction, a stop sign flagged where none existed) and say those detections lowered the weekly scores that decide their bonuses and prizes. The accounts are attributed, Amazon's response and appeal process are recorded, and the amount lost is left unknown.","reviewed_on":"2026-10-27"},"ai_involvement":{"basis":"Motherboard describes the Netradyne cameras as AI-powered devices that detect driving events (following distance, stop-sign and signal violations, distracted driving) and upload them to a score. The drivers say the cameras' own detections were wrong: a car cutting in was recorded as unsafe following distance, a glance at a mirror as distraction, and a stop sign was flagged on a road that had none. Those detections entered the weekly scores that, according to the drivers and Amazon's internal scorecard document, decide bonuses and prizes.","status":"reported"},"person_relations":["made_claim_about"]},"name":"Amazon delivery drivers say Netradyne AI cameras in their vans flagged driving 'events' they did not commit, lowering the weekly scores that set bonuses","summary":"In September 2021 Motherboard reported accounts from six Amazon delivery drivers in five US states and the owner of an Amazon delivery company, who said the AI-powered Netradyne cameras Amazon had installed in its delivery vans from early 2021 regularly registered driving 'events' that were beyond their control or were not unsafe driving: being cut off by another car, glancing at a side mirror, stopping past a stop sign to see around a bush, or a stop sign flagged on a dirt road with no sign. Each event fed a weekly safe-driving score that, according to the drivers and an internal Amazon document Motherboard obtained, helped decide drivers' bonuses and prizes and delivery companies' bonuses. A driver in Los Angeles said the camera incorrectly penalised him and that requests to see the photos flagged as events went unanswered; a former driver in Texas said events that did not happen affected his score, which decided prizes from his delivery company. Amazon said the technology gives drivers real-time safety alerts, that accidents and violations had fallen since it was installed, and that its staff manually review appealed events so that erroneous ones do not affect drivers. Netradyne did not respond to Motherboard.","incidentDate":"2021-01-01","incidentKind":"ongoing_experience","incidentDatePrecision":"year","exposurePattern":"repeated_interactions","reportedDate":"2021-09-20","aiSystem":"Netradyne AI-powered four-lens cameras installed in Amazon-branded delivery vans, which detect driving 'events' such as following distance, stop-sign and signal violations and distracted driving, upload the footage and feed Amazon's weekly driver and delivery-company scores","aiProduct":"Netradyne cameras","severity":"low","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["professional_harm","financial_loss"],"harmOutcomeSummary":"Drivers told Motherboard that the AI cameras registered events they did not commit or that were not unsafe, lowering the weekly scores that decided their bonuses and prizes; one said winning prizes 'went downhill' once the cameras came, and another described the penalties as upsetting.","frameworkFacets":[],"causationStatus":"alleged","participantUsersAffectedMin":0,"otherPeopleHarmedMin":2,"affectedCountStatus":"partial","affectedCountEvidence":"Two drivers are counted: the Los Angeles driver, who said the camera incorrectly penalised him in the data used for his weekly evaluation and bonus, and the former Sugar Land driver, who said events that did not happen affected his score and his prizes. Motherboard spoke to six drivers and a delivery-company owner who described false or unfair events more generally; the others are not counted because a personal score or pay consequence is not reported for each. The fleet size and driver numbers in the article are not counts of harmed people. The drivers are not counted as direct AI users.","victimAgeRange":"adult","jurisdiction":"US","platformType":"other","outcomeStatus":"unknown","primarySourceUrl":"https://www.vice.com/en/article/amazons-ai-cameras-are-punishing-drivers-for-mistakes-they-didnt-make/","primarySourceLabel":"Motherboard (VICE), 20 September 2021: Amazon's AI cameras are punishing drivers for mistakes they didn't make","firstPublishedAt":"2026-10-27T03:09:21.159219+00:00","updatedAt":"2026-10-27T03:09:21.159219+00:00","scopeVersion":"facts-v3","tags":["work","delivery-drivers","workplace-monitoring","in-vehicle-camera","driver-scores","pay","institutional-use"]},{"id":"2021-telangana-samagra-vedika-algorithm-wrongly-tagged-poor-families-as-car-owners-food-security-cards-denied","caseFacts":{"claims":[{"id":"c1","status":"reported","evidence":[{"locator":"'started arming the officials with Samagra Vedika, an algorithmic system that consolidates citizens'; 'the officials were mandated to check whether the algorithmic system approved the eligibility of the applicant before making their own decision'; 'They could either go with the algorithm'","relation":"supports","source_id":"s1"}],"assertion":"Since 2016 Telangana has used Samagra Vedika, a system that consolidates residents' data from several government databases, to check welfare eligibility; officials processing food security cards were mandated to check whether the system approved an applicant before deciding, and could depart from it only by giving reasons and evidence.","causal_attribution":"Background on the system and how its output entered officials' decisions."},{"id":"c2","status":"reported","evidence":[{"locator":"'Samagra Vedika uses'; 'to uniquely identify a person'; 'If it finds a match close enough violating any of the criteria, it tags the claimant as ineligible'","relation":"supports","source_id":"s1"}],"assertion":"Al Jazeera reports that Samagra Vedika uses machine learning and entity resolution technology to identify a person across databases, and tags a claimant as ineligible when it finds a close enough match violating a criterion such as owning a four-wheeler.","causal_attribution":"The description of the technology is Al Jazeera's, quoting terms whose origin the article does not state; the government describes it as using big data."},{"id":"c3","status":"reported","evidence":[{"locator":"'mistook her late husband'; 'and the authorities accepted the algorithm'; 'finally rejecting it in 2021 because they claimed she possessed a four-wheeler'; 'The authorities did not trust her'; 'they believed their algorithm'","relation":"supports","source_id":"s1"}],"assertion":"According to Al Jazeera, the system mistook a widow's late husband, a rickshaw puller, for a car owner with a similar name; her food security card renewal application was rejected in 2021 because she was said to possess a four-wheeler, and that the authorities believed their algorithm rather than her.","causal_attribution":"Al Jazeera attributes the rejection to the system's wrong match and officials' acceptance of it."},{"id":"c4","status":"reported","evidence":[{"locator":"'found its real owner'; 'the officials agreed there was an algorithmic error but said that her application could not be considered because her total family income exceeded the eligibility limit even though that was not the case'; 'who has been denied ration for more than seven years, is still waiting'","relation":"supports","source_id":"s1"}],"assertion":"After she traced the vehicle's real owner, officials agreed there had been an algorithmic error but said that her application could not be considered because family income exceeded the limit, which Al Jazeera says was not the case; she had been denied the rations for more than seven years when the article was published.","causal_attribution":"The officials' acknowledgement of an algorithmic error is reported by Al Jazeera; the continued denial rests on a different, disputed ground."},{"id":"c5","status":"reported","evidence":[{"locator":"'an algorithm has tagged the family as owning a car, denying them access to subsidised food grains'; 'The family applied for a food security card in 2018 but was rejected in 2021'; 'Instead of three rupees, we spend 10 for every kilogramme of rice'; 'the petitioner is eligible'","relation":"supports","source_id":"s1"}],"assertion":"A second family, whose husband cannot drive, applied in 2018 and was rejected in 2021 for possessing a four-wheeler they do not own; Al Jazeera's caption says an algorithm tagged the family as owning a car, and the woman says the family pays more for the same rice bought from dealers. In November 2023 the High Court of Telangana said the petitioner is eligible whenever the state issues new cards.","causal_attribution":"The algorithmic tag is stated in an Al Jazeera photo caption credited to The Reporters' Collective; the High Court remark is reported, not read in the order itself."},{"id":"c6","status":"reported","evidence":[{"locator":"'The petition lists around 10 cases of wrongful exclusions'; 'Al Jazeera visited three of those and can confirm they were wrongly tagged by Samagra Vedika'","relation":"supports","source_id":"s1"}],"assertion":"Al Jazeera says it visited three of the roughly ten wrongful-exclusion cases listed in a Supreme Court petition and confirmed they were wrongly tagged by Samagra Vedika.","causal_attribution":"Al Jazeera's own verification; the three cases are not identified."},{"id":"c7","status":"disputed","evidence":[{"locator":"'The government has previously said that the technology is of'; 'It has also said that the error of tagging a vehicle or a house to the wrong person happens in less than five percent of all cases'; 'very high levels of accuracy'","relation":"supports","source_id":"s1"}],"assertion":"The Telangana government has said the technology is of high precision, that wrong tagging of a vehicle or house occurs in less than five per cent of cases and has mostly been corrected, and an official said verifications found very high levels of accuracy.","causal_attribution":"Government counter-position; it does not address the individual cases."}],"effects":[{"label":"food security card applications rejected after the system wrongly tagged families as car owners; years without subsidised rations","claim_id":"c3","direction":"negative"}],"sources":[{"id":"s1","url":"https://www.aljazeera.com/economy/2024/1/24/how-an-algorithm-denied-food-to-thousands-of-poor-in-indias-telangana","kind":"news_report","access":"read","language":"en","translation_note":"Read in English on 2026-10-24 (full article). Reported by Tapasya, Kumar Sambhav and Divij Joshi with The Reporters' Collective and the Pulitzer Center's AI Accountability Network; the photo captions are courtesy of The Reporters' Collective.","independence_group":"al-jazeera-reporters-collective-samagra-vedika-investigation"}],"version":1,"ai_roles":["institutional_use"],"contexts":["public_services","finance"],"unknowns":["Which three petition cases Al Jazeera verified, and how many wrongful exclusions the system itself caused.","Whether the widow's card was later issued, and whether the second family has received a card since November 2023.","How the matching works in detail; the state withheld the source code and data formats.","Why the widow's card was first cancelled in 2016."],"geography":{"basis":"Al Jazeera reports from Hyderabad that both families live there and applied to the Telangana government; the Supreme Court of India and the High Court of Telangana heard related petitions.","court_countries":["IN"],"event_countries":["IN"],"affected_person_countries":["IN"]},"publication":{"basis":"Published as a concrete adverse public decision informed by an automated matching system: Al Jazeera reports that Samagra Vedika wrongly matched a widow's late husband to a car owner and tagged another family as owning a car, and that officials rejected their food security cards on those tags; officials later acknowledged an algorithmic error in the widow's case.","reviewed_on":"2026-10-24"},"ai_involvement":{"basis":"Al Jazeera reports that Samagra Vedika matched a widow's late husband to a car owner with a similar name and tagged her family as owning a four-wheeler, that officials (mandated to check the system's approval before deciding) accepted the tag and rejected her food security card in 2021, and that they later agreed there had been an algorithmic error. It describes the system as using machine learning and entity resolution to match people across databases; the government describes it as using big data and disputes the error rate. The source code and data formats were withheld from the reporters.","status":"supported"},"person_relations":["made_claim_about","informed_decision_about"]},"name":"Al Jazeera investigation says Telangana's Samagra Vedika system wrongly matched poor families to car owners, and officials denied them food subsidy cards","summary":"An Al Jazeera investigation published on 24 January 2024, produced with The Reporters' Collective and the Pulitzer Center's AI Accountability Network, reports that Samagra Vedika, a system the Telangana government uses to consolidate residents' data and check welfare eligibility, wrongly tagged poor families in Hyderabad as owning cars, and that officials relied on those tags to deny them food security cards (subsidised rice). Al Jazeera says the system uses machine learning and entity resolution to match people across databases, and that since 2016 officials have been mandated to check whether the system approved an applicant before deciding. In one case it reports that the system mistook a widow's late husband, a rickshaw puller, for a car owner with a similar name; her renewal application was rejected in 2021 for possessing a four-wheeler. After she traced the vehicle's real owner, officials agreed there had been an algorithmic error but said her family income exceeded the limit, which Al Jazeera says was not the case; she had been without the subsidised rations for more than seven years. A second family, whose husband cannot drive, was rejected in 2021 for possessing a four-wheeler; in November 2023 the High Court of Telangana said the petitioner is eligible whenever new cards are issued. The government says the technology is highly precise and that wrong vehicle or house tags occur in under five per cent of cases and have mostly been corrected.","incidentDate":"2021-01-01","incidentKind":"bounded_series","incidentDatePrecision":"year","exposurePattern":"unknown","reportedDate":"2024-01-24","aiSystem":"Samagra Vedika, the Telangana government's data-integration and profiling system developed by Posidex Technologies, which Al Jazeera says uses machine learning and entity resolution technology to identify people across government databases and tag welfare applicants as ineligible","aiProduct":"Samagra Vedika","severity":"medium","verificationStatus":"credible","harmCategories":[],"harmOutcomes":["financial_loss","other_material_harm"],"harmOutcomeSummary":"According to an Al Jazeera investigation, Telangana's Samagra Vedika system wrongly tagged poor families as car owners and officials denied them food security cards on that basis; a widow had been without subsidised rations for over seven years and another family pays market prices for rice.","frameworkFacets":[],"causationStatus":"supported","participantUsersAffectedMin":0,"otherPeopleHarmedMin":2,"affectedCountStatus":"partial","affectedCountEvidence":"Two applicants described with their rejections: the widow and the woman whose family was rejected in 2021 (members of their households are not counted separately). Al Jazeera says it visited three of about ten petition cases and confirmed they were wrongly tagged, without listing them, and gives state re-verification figures that it does not attribute to the system alone; these are not counted.","victimAgeRange":"adult","jurisdiction":"IN","platformType":"other","outcomeType":"media_coverage","outcomeStatus":"ongoing","primarySourceUrl":"https://www.aljazeera.com/economy/2024/1/24/how-an-algorithm-denied-food-to-thousands-of-poor-in-indias-telangana","primarySourceLabel":"Al Jazeera, How an algorithm denied food to thousands of poor in India's Telangana, 24 January 2024","firstPublishedAt":"2026-10-24T03:08:52.234671+00:00","updatedAt":"2026-10-24T03:08:52.234671+00:00","scopeVersion":"facts-v3","tags":["welfare-eligibility-algorithm","entity-resolution","food-security","wrong-match","public-services"]}]}