{"meta":{"exportedAt":"2026-10-27T06:26:41.462Z","formatVersion":2,"selection":{"q":"financial_loss","system":"","harm":"","context":"","country":"","role":"","relation":"","evidence":"","year":"2021","response":"","severity":"","verification":"","view":"incidents","sort":"added"},"totalIncidents":2,"coverage":{"cases":2,"countries":2,"languages":1,"unknownLocation":0,"locationPending":0,"unknownLanguage":0,"unknownDate":0,"lawsuits":0,"regulatory":0,"minors":0,"coreRelations":0,"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":"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"]}]}