{"attribution":{"source":"AI Incident Database (Responsible AI Collaborative)","license":"CC BY-SA 4.0","license_url":"https://creativecommons.org/licenses/by-sa/4.0/","citation":"McGregor, S. (2021). Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. Proceedings of the AAAI Conference on Artificial Intelligence (IAAI-21).","snapshot_date":"2026-09-07"},"exported_at":"2026-09-11"}
{"rows":[{"incident_id":1401,"occurred_on":"2026-02-27","title":"Washington State DOL's AI Phone System Reportedly Failed to Provide Spanish-Language Service to Callers Requesting Spanish","description":"For months, callers to the Washington State Department of Licensing who selected Spanish reportedly received AI-generated English responses spoken with a Spanish accent rather than actual Spanish-language service. The agency reportedly apologized and said staff configuration caused the error, which purportedly created accessibility problems for callers seeking language support.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"Human","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Washington State Department Of Licensing, Amazon"],"developers":["Amazon"],"harmed":["Spanish Language Speakers, General Public Of Washington State, General Public"],"report_count":5},{"incident_id":1305,"occurred_on":"2025-12-05","title":"UK Facial Recognition System Reportedly Exhibits Higher False Positive Rates for Black and Asian Subjects","description":"UK government testing of police facial recognition technology reportedly found significantly higher false positive identification rates for Black and Asian individuals compared with white subjects, with particularly elevated error rates for Black women. The findings reportedly emerged from analysis of retrospective searches of the police national database and were disclosed by the Home Office amid plans for expanded national deployment.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Home Office, Metropolitan Police, Government Of The United Kingdom, Law Enforcement, British Law Enforcement"],"developers":["Unknown Facial Recognition Technology Developers"],"harmed":["General Public, General Public Of The United Kingdom, Minorities In The United Kingdom, Black People In The United Kingdom, Asian People In The United Kingdom, Epistemic Integrity, National Security And Intelligence Stakeholders"],"report_count":4},{"incident_id":808,"occurred_on":"2024-10-11","title":"Infinite Campus AI-Driven Student Risk Model Leads to Cuts in Support for Nevada's Low-Income Schools","description":"An AI system developed by Infinite Campus and deployed by Nevada to identify at-risk students reportedly led to a sharp reduction in the number classified as needing support, dropping from 270,000 to 65,000. The reclassification allegedly caused significant budget cuts in schools serving low-income populations. The drastic reduction in identified at-risk students reportedly left thousands of vulnerable children without resources and support.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Nevada Department of Education"],"developers":["Infinite Campus"],"harmed":["Students","Somerset Academy","Nevada school districts","Minors","Mater Academy of Nevada","Educational communities","Economically vulnerable students in Nevada","Economically vulnerable people"],"report_count":1},{"incident_id":815,"occurred_on":"2024-10-06","title":"Police Use of Facial Recognition Software Causes Wrongful Arrests Without Defendant Knowledge","description":"Police departments across the U.S. have used facial recognition software to identify suspects in criminal investigations, leading to multiple false arrests and wrongful detentions. The software's unreliability, especially in identifying people of color, has resulted in misidentifications that were not disclosed to defendants. In some cases, individuals were unaware that facial recognition played a role in their arrest, violating their legal rights and leading to unjust detentions.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["West New York PD","Police departments","Pflugerville PD","NYPD","Miami PD","Law enforcement","Jefferson Parish Sheriff’s Office","Facial recognition system deployers"],"developers":["Facial recognition system developers","Clearview AI"],"harmed":["Quran Reid","Privacy","People misidentified by facial recognition systems","General public of the United States","General public","Francisco Arteaga","Biometric data subjects"],"report_count":2},{"incident_id":738,"occurred_on":"2024-06-23","title":"Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud","description":"A Department for Work and Pensions (DWP) algorithm wrongly flagged over 200,000 UK housing benefit claims as high risk, resulting in unnecessary investigations. Two-thirds of these flagged claims were legitimate, causing wasted public funds and stress for claimants. Despite initial success in a pilot, the algorithm's real-world performance fell short. This incident highlights the risks of overreliance on automated systems in welfare administration.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Department For Work And Pensions"],"developers":["Department For Work And Pensions"],"harmed":["Uk General Public, Uk Housing Benefit Claimants"],"report_count":5},{"incident_id":691,"occurred_on":"2024-05-25","title":"Facewatch Reported to Have Wrongfully Flagged Home Bargains Customer as Shoplifter","description":"A facial-recognition software used by the British variety store Home Bargains is alleged to have misidentified \"Sara\" as a shoplifter, leading to staff searching her bag, escorting her from the premises, and banning her from the store. After, Facewatch is reported to have admitted its error to Sara. Facewatch is used by a number of different British stores.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Home Bargains"],"developers":["Facewatch"],"harmed":["Sara, Home Bargains Customers, General Public"],"report_count":2},{"incident_id":732,"occurred_on":"2024-02-12","title":"Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations","description":"Researchers at Cornell reportedly found that OpenAI's Whisper, a speech-to-text system, can hallucinate violent language and fabricated details, especially with long pauses in speech, such as from those with speech impairments. Analyzing 13,000 clips, they determined 1% contained harmful hallucinations. These errors pose risks in hiring, legal trials, and medical documentation. The study suggests improving model training to reduce these hallucinations for diverse speaking patterns.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Whisper, Organizations Integrating Whisper Into Customer Service Systems, Openai, Companies Using Whisper, Whisper Users"],"developers":["Openai"],"harmed":["Users Whose Speech Is Misinterpreted By Whisper, Professionals Relying On Accurate Transcriptions, Individuals With Speech Impairments, General Public, People With Disabilities"],"report_count":1},{"incident_id":692,"occurred_on":"2024-02-01","title":"London Metropolitan Police's Facial Recognition Technology Reportedly Misidentified Shaun Thompson as Suspect Leading to Arrest","description":"Sometime in February 2024, Shaun Thompson is reported to have walked by one of the London Metropolitan Police's facial recognition technology vans near London Bridge. He was almost immediately arrested because the technology is reported to have misidentified him as a suspect in an unrelated and unspecified crime.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Metropolitan Police Service","Law enforcement","Facial recognition system deployers"],"developers":["Facial recognition system developers"],"harmed":["Shaun Thompson","General public of the United Kingdom","General public"],"report_count":3},{"incident_id":592,"occurred_on":"2023-02-16","title":"Facial Recognition Misidentifies Pregnant Woman Leading to False Arrest in Detroit","description":"Porcha Woodruff was arrested and subsequently had charges dropped due to an unreliable facial recognition match. Despite being visibly pregnant, she was implicated in a robbery and carjacking based on an outdated photo used in a lineup.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Law enforcement","Detroit Police Department"],"developers":["Unknown"],"harmed":["Porcha Woodruff"],"report_count":3},{"incident_id":440,"occurred_on":"2022-11-25","title":"Louisiana Police Wrongfully Arrested Black Man Using False Face Match","description":"Louisiana police reportedly used a false facial recognition match and secured an arrest warrant for a Black man for thefts he did not commit.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Baton Rouge Police Department"],"developers":["Morphotrak","Clearview AI"],"harmed":["Randall Reid","Black people in Louisiana","Black people"],"report_count":6},{"incident_id":515,"occurred_on":"2022-11-25","title":"Facial Recognition Error Reportedly Leads to Wrongful Arrest of Georgia Man and $200K Settlement in Louisiana","description":"In November 2022, Randal \"Quran\" Reid was arrested in Georgia based on warrants from Louisiana that reportedly stemmed from a purportedly faulty facial recognition match using Clearview AI. Despite reportedly having never visited Louisiana, Reid was jailed for six days before authorities withdrew the warrants. No corroborating evidence had been gathered, and the technology's use was omitted from legal documents. In May 2025, Jefferson Parish settled with Reid for $200,000 in a federal civil righ","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Jefferson Parish Sheriff’s Office"],"developers":["Clearview AI"],"harmed":["Randal Quran Reid"],"report_count":3},{"incident_id":598,"occurred_on":"2022-11-25","title":"False Arrest of Georgia Man Due to Louisiana Police's Faulty Facial Recognition Technology","description":"The Jefferson Parish Sheriff’s Office in Louisiana relied on facial recognition technology to identify suspects for the alleged theft of luxury purses, resulting in a man in Georgia, Randal Reid, being arrested. However, the technology produced a false match, leading to Reid's arrest and subsequent release. This incident highlights the potential pitfalls of facial recognition technology in law enforcement.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Law enforcement","Jefferson Parish Sheriff’s Office","Facial recognition system deployers"],"developers":["Unknown","Facial recognition system developers"],"harmed":["Randal Reid","Minority groups","Black people"],"report_count":1},{"incident_id":168,"occurred_on":"2022-03-01","title":"Collaborative Filtering Prone to Popularity Bias, Resulting in Overrepresentation of Popular Items in the Recommendation Outputs","description":"Collaborative filtering prone to popularity bias, resulting in overrepresentation of popular items in the recommendation outputs.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Facebook, Linkedin, Youtube, Twitter, Netflix"],"developers":["Facebook, Linkedin, Youtube, Twitter, Netflix"],"harmed":["Facebook Users, Linkedin Users, Youtube Users, Netflix Users, X (Twitter) Users"],"report_count":2},{"incident_id":400,"occurred_on":"2022-02-23","title":"Google Search Reportedly Returned Fewer Results for Abortion Services in Rural Areas","description":"Google Search reportedly returned fewer abortion clinics for searches from poorer and rural areas, particularly ones with Targeted Regulation of Abortion Providers (TRAP) laws.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Google"],"developers":["Google"],"harmed":["Women seeking abortion services","women having unexpected or crisis pregnancies","Women and girls","Women","Pregnant women","Pregnant patients","Pregnant individuals","Patients"],"report_count":1},{"incident_id":163,"occurred_on":"2021-11-21","title":"Facebook’s Hate Speech Detection Algorithms Allegedly Disproportionately Failed to Remove Racist Content towards Minority Groups","description":"Facebook’s hate-speech detection algorithms was found by company researchers to have under-reported less common but more harmful content that was more often experienced by minority groups such as Black, Muslim, LGBTQ, and Jewish users.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Facebook"],"developers":["Facebook"],"harmed":["Facebook Users, Minority Groups"],"report_count":2},{"incident_id":108,"occurred_on":"2021-07-10","title":"Skating Rink’s Facial Recognition Cameras Misidentified Black Teenager as Banned Troublemaker","description":"A Black teenager living in Livonia, Michigan was incorrectly stopped from entering a roller skating rink after its facial-recognition cameras misidentified her as another person who had been previously banned for starting a skirmish with other skaters.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["arts, entertainment and recreation"],"countries":["US"],"deployers":["Riverside Arena Skating Rink"],"developers":["Unknown"],"harmed":["Lamya Robinson, Black Livonia Residents"],"report_count":3},{"incident_id":158,"occurred_on":"2021-02-01","title":"Remote Proctoring Facial-Detection Software Reportedly Failed to Detect Black Student During Lab Quiz","description":"In February 2021, a Black college student, Amaya Ross, reportedly tried to take a remote biology lab quiz using proctoring software that could not detect her face. Ross said she spent 45 minutes changing lights, shades, position, and background before pointing an LED flashlight at her face so the app would work; the quiz itself was only 30 minutes.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Unnamed Ohio College"],"developers":["Unknown Remote Proctoring Software Developers"],"harmed":["University Students, Universities, Students, Educational Communities, Black Test Takers, Black Students, Amaya Ross"],"report_count":1},{"incident_id":131,"occurred_on":"2020-12-04","title":"Proctoring Algorithm in Online California Bar Exam Flagged an Unusually High Number of Alleged Cheaters","description":"The proctoring algorithm used in a California bar exam cited a third of thousands of applicants as cheaters, resulting in allegations where exam takers were instructed to prove otherwise without seeing their incriminating video evidence.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["education","professional, scientific and technical activities"],"countries":["US"],"deployers":["California Bar'S Committee Of Bar Examiners"],"developers":["Examsoft"],"harmed":["California Bar Exam Takers, Flagged California Bar Exam Takers"],"report_count":2},{"incident_id":81,"occurred_on":"2020-10-21","title":"Researchers find evidence of racial, gender, and socioeconomic bias in chest X-ray classifiers","description":"A study by the University of Toronto, the Vector Institute, and MIT showed the input databases that trained AI systems used to classify chest X-rays led the systems to show gender, socioeconomic, and racial biases.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Pre-deployment","harm_level":"none","sectors":["human health and social work activities"],"countries":[],"deployers":["Mount Sinai Hospitals"],"developers":["Qure.ai","Google","DarwinAI","Aidoc"],"harmed":["Women and girls","Women","Patients","Medicaid beneficiaries","Hispanic patients","Economically vulnerable patients"],"report_count":1},{"incident_id":87,"occurred_on":"2020-10-07","title":"UK passport photo checker shows bias against dark-skinned women","description":"UK passport photo checker shows bias against dark-skinned women.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["public administration"],"countries":["GB"],"deployers":["UK Home Office","Government of the United Kingdom"],"developers":["UK Home Office","Government of the United Kingdom"],"harmed":["Women and girls","Women","dark-skinned women","dark-skinned people"],"report_count":1},{"incident_id":275,"occurred_on":"2020-06-11","title":"Facebook’s Moderation Algorithm Banned Users for Historical Evidence of Slavery","description":"Facebook’s automated content moderation was acknowledged by a company spokesperson to have erroneously censored and banned Australian users from posting an article containing a 1890s photo of Aboriginal men in chains over nudity as historical evidence of slavery in Australia.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Facebook"],"developers":["Facebook"],"harmed":["Facebook Users Sharing Photo Evidence Of Slavery, Facebook Users"],"report_count":2},{"incident_id":140,"occurred_on":"2020-06-01","title":"University of Toronto's ProctorU Deployment Reportedly Disadvantaged BIPOC Students During Exam Check-Ins","description":"University of Toronto students reported that ProctorU and other online exam-monitoring services created discriminatory and stressful check-in experiences for BIPOC students during remote exams. One U of T student said ProctorU's identity-verification process often failed to recognize her passport, forcing manual checks and consuming exam check-in time. ProctorU said human proctors made final identity and integrity decisions.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["education"],"countries":["CA"],"deployers":["University Of Toronto"],"developers":["Proctoru"],"harmed":["University Students, University Of Toronto Students, Students, Educational Communities, Students Of Color"],"report_count":1},{"incident_id":138,"occurred_on":"2020-03-23","title":"University of Illinois' Proctorio Remote-Proctoring Deployment Reportedly Raised Student Rights Concerns","description":"Beginning in March 2020, the University of Illinois Urbana-Champaign deployed Proctorio for remote exam proctoring after the COVID-19 shift to online instruction. Students and faculty raised concerns that the software surveilled students' homes and devices, created accessibility barriers, increased testing anxiety, and could flag students when facial-detection tools failed to detect their faces, with particular concern for students of color. UIUC later declined to renew its emergency contract.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["University Of Illinois Urbana Champaign"],"developers":["Proctorio"],"harmed":["Students, University Students, Educational Communities, University Of Illinois Urbana Champaign Students, Students Of Color, Students With Disabilities"],"report_count":6},{"incident_id":102,"occurred_on":"2020-03-23","title":"Personal voice assistants struggle with black voices, new study shows","description":"A study found that voice recognition tools from Apple, Amazon, Google, IBM, and Microsoft disproportionately made errors when transcribing black speakers.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["administrative and support service activities","information and communication"],"countries":["US"],"deployers":["Microsoft, Ibm, Google, Apple, Amazon"],"developers":["Microsoft, Ibm, Google, Apple, Amazon"],"harmed":["Black People"],"report_count":2},{"incident_id":74,"occurred_on":"2020-01-30","title":"Detroit Police Allegedly Wrongfully Arrested Black Man Due to Purportedly Faulty Facial Recognition Technology","description":"A Black man was allegedly wrongfully detained by the Detroit Police Department as a result of a purportedly false facial recognition technology (FRT) result.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["law enforcement"],"countries":["US"],"deployers":["Detroit Police Department"],"developers":["DataWorks Plus"],"harmed":["Robert Julian-Borchak Williams","Black people in Detroit"],"report_count":11},{"incident_id":214,"occurred_on":"2020-01-02","title":"SN Technologies Reportedly Lied to a New York State School District about Its Facial and Weapon Detection Systems’ Performance","description":"SN Technologies allegedly misled Lockport City Schools about the performance of its AEGIS face and weapons detection systems, downplaying error rates for Black faces and weapon misidentification.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm near-miss","sectors":["education","law enforcement","public administration"],"countries":["US"],"deployers":["Lockport City School District"],"developers":["SN Technologies"],"harmed":["Students","Epistemic integrity","Educational communities","Black students"],"report_count":1},{"incident_id":417,"occurred_on":"2019-11-15","title":"Facebook Feed Algorithms Exposed Low Digitally Skilled Users to More Disturbing Content","description":"Facebook feed algorithms were known by internal research to have harmed people having low digital literacy by exposing them to disturbing content they did not know how to avoid or monitor.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Facebook"],"developers":["Facebook"],"harmed":["Low Digitally Skilled Facebook Users"],"report_count":4},{"incident_id":189,"occurred_on":"2019-10-15","title":"Opaque Fraud Detection Algorithm by the UK’s Department of Work and Pensions Allegedly Discriminated against People with Disabilities","description":"People with disabilities were allegedly disproportionately targeted by a benefit fraud detection algorithm which the UK’s Department of Work and Pensions was urged to disclose.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["UK Department of Work and Pensions"],"developers":["UiPath"],"harmed":["People with disabilities"],"report_count":6},{"incident_id":386,"occurred_on":"2019-07-03","title":"Amazon’s \"Time Off Task\" System Made False Assumptions about Workers' Time Management","description":"Amazon’s warehouse worker “time off task\" (TOT) tracking system was used to discipline and dismiss workers, falsely assuming workers to have wasted time and failing to account for breaks or equipment issues.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Amazon"],"developers":["Amazon"],"harmed":["Amazon warehouse workers"],"report_count":3},{"incident_id":288,"occurred_on":"2019-01-30","title":"New Jersey Police Wrongful Arrested Innocent Black Man via FRT","description":"Woodbridge Police Department falsely arrested an innocent Black man following a misidentification by their facial recognition software, who was jailed for more than a week and paid thousands of dollar for his defense.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Woodbridge Police Department"],"developers":["Unknown"],"harmed":["Nijeer Parks"],"report_count":4},{"incident_id":114,"occurred_on":"2018-07-26","title":"Amazon's Rekognition Falsely Matched Members of Congress to Mugshots","description":"Rekognition's face comparison feature was shown by the ACLU to have misidentified members of congress, and particularly members of colors, as other people who have been arrested using a mugshot database built on publicly available arrest photos.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication","law enforcement"],"countries":["US"],"deployers":["Amazon"],"developers":["Amazon"],"harmed":["Rekognition Users, Arrested People"],"report_count":1},{"incident_id":517,"occurred_on":"2018-02-15","title":"Man Arrested For Sock Theft by False Facial Match Despite Alibi","description":"A man was arrested for theft of socks from a TJ Maxx store under the guise of an eyewitness ID case, after the local police asked the store's security guard to confirm the facial recognition match produced using surveillance footage, despite him having an alibi at the time of the theft.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["New York Police Department"],"developers":["Unknown"],"harmed":["Unknown"],"report_count":2},{"incident_id":418,"occurred_on":"2017-03-13","title":"Uber Locked Indian Drivers out of Accounts Allegedly Due to Facial Recognition Fails","description":"Uber drivers in India reported being locked out of their accounts allegedly due to Real-Time ID Check's facial recognition failing to recognize appearance changes or faces in low lighting conditions.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Uber"],"developers":["Uber","Azure Cognitive Services"],"harmed":["Uber drivers in India"],"report_count":3},{"incident_id":48,"occurred_on":"2016-12-07","title":"Passport checker Detects Asian man's Eyes as Closed","description":"New Zealand passport robot reader rejects the application of an applicant with Asian descent and says his eyes are closed.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unequal performance across groups","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["public administration"],"countries":["NZ"],"deployers":["New Zealand"],"developers":["New Zealand"],"harmed":["Asian People"],"report_count":20}]}