{"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":193,"occurred_on":"2013-11-27","title":"Excessive Automated Monitoring Alerts Ignored by Staff, Resulting in Private Data Theft of Seventy Million Target Customers","description":"Alerts about a Target data breach were ignored by Minneapolis Target’s staff reportedly due to them being included with many other potential false alerts, and due to some of the company’s network infiltration alerting systems being off to reduce such false alerts, causing private data theft for millions of customers.  ","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Target"],"developers":["Fireeye"],"harmed":["Target, Target Customers"],"report_count":1},{"incident_id":373,"occurred_on":"2013-10-01","title":"Michigan's Unemployment Benefits Algorithm MiDAS Issued False Fraud Claims to Thousands of People","description":"Michigan’s MiDAS system falsely accused over 34,000 people of unemployment fraud from 2013 to 2015, which reportedly caused financial ruin for many. The automated system was designed to cut costs, but it adjudicated fraud cases without human oversight. That led to an 85% error rate. Victims faced wage garnishments, some lost homes, and some faced bankruptcy. Despite early warnings, Michigan’s UIA defended MiDAS until lawsuits and federal pressure forced reforms. Legislators have been seeking com","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Michigan Unemployment Insurance Agency"],"developers":["Fast Enterprises, Csg Government Solutions"],"harmed":["Unemployed Michigan Residents Falsely Accused Of Fraud, Michigan Residents Who Faced Bankruptcy Or Foreclosure Due To Midas"],"report_count":14},{"incident_id":409,"occurred_on":"2013-09-13","title":"Facial Recognition Researchers Allegedly Used YouTube Videos of Transgender People Without Consent","description":"YouTube videos of transgender people used by researchers to study facial recognition during gender transitions were allegedly used and distributed without permission.","mit_domain":"Privacy & Security","mit_subdomain":"Compromise of privacy by obtaining, leaking or correctly inferring sensitive information","entity":"Human","intent":"Intentional","timing":"Post-deployment","harm_level":"none","sectors":["professional, scientific and technical activities"],"countries":[],"deployers":["University of North Carolina Wilmington","Karl Ricanek","Gayathri Mahalingam"],"developers":["University of North Carolina Wilmington","Karl Ricanek","Gayathri Mahalingam"],"harmed":["YouTubers","YouTube users","Transgender YouTubers","transgender people","Social media users","Privacy","Biometric data subjects"],"report_count":3},{"incident_id":196,"occurred_on":"2013-09-01","title":"Compromise of National Biometric ID Card System Leads to Reverification and Change of Status","description":"When the leader of the Afghan Taliban was found possessing a valid ID card in the Pakistani national biometric identification database system, Pakistan launch a national re-verification campaign that is linked to numerous changes in recognition status and loss of services.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Pakistan National Database And Registration Authority"],"developers":["Pakistan National Database And Registration Authority"],"harmed":["Pakistani Citizens"],"report_count":5},{"incident_id":280,"occurred_on":"2013-07-30","title":"Coffee Meets Bagel’s Algorithm Reported by Users Disproportionately Showing Them Matches of Their Own Ethnicities Despite Selecting “No Preference”","description":"Users selecting “no preference” were shown by Coffee Meets Bagels’s matching algorithm more potential matches with the same ethnicity, which was acknowledged and justified by its founder as a means to maximize connection rate without sufficient user information.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Coffee Meets Bagel"],"developers":["Coffee Meets Bagel"],"harmed":["Coffee Meets Bagel Users Having No Ethnicity Preference, Coffee Meets Bagel Users"],"report_count":2},{"incident_id":19,"occurred_on":"2013-01-23","title":"Sexist and Racist Google Adsense Advertisements","description":"Advertisements chosen by Google Adsense are reported as producing sexist and racist results.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["information and communication"],"countries":["US"],"deployers":["Google"],"developers":["Google"],"harmed":["Women and girls","Women","Minority groups"],"report_count":27}]}