{"meta":{"exportedAt":"2026-11-02T07:17:51.113Z","formatVersion":2,"selection":{"q":"welfare","system":"","harm":"","context":"","country":"","role":"","relation":"contextual","evidence":"","year":"","response":"","severity":"","verification":"","view":"incidents","sort":"added"},"totalIncidents":2,"coverage":{"cases":2,"countries":1,"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":"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":"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"]}]}