{"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":536,"occurred_on":"2012-12-10","title":"NJ Transit's Use of Modeling Software Miscalculated Storm Surge Threat Level","description":"New Jersey Transit's use of a federal government storm modeling software underestimated the threat of storm surges to the Meadows Maintenance Complex, leaving millions of dollars worth of equipment in the rail yard before Hurricane Sandy struck.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"Human","intent":"Unintentional","timing":"Pre-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["New Jersey Transit"],"developers":["National Weather Service"],"harmed":["New Jersey Transit, New Jersey Transit Passengers"],"report_count":2},{"incident_id":135,"occurred_on":"2012-12-01","title":"UT Austin's GRADE Algorithm Reportedly Reduced Review of Lower-Scored PhD Applicants Amid Bias Concerns","description":"From the 2013 through 2019 admissions cycles, UT Austin's Department of Computer Science used GRADE, a statistical machine-learning system trained on past admissions decisions, to score and organize PhD applications. Critics said the system could reproduce historical admissions inequities and reduce attention to lower-scored applicants, while UT Austin said human reviewers still evaluated each file and later discontinued the tool.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"none","sectors":["education"],"countries":["US"],"deployers":["University of Texas at Austin's Department of Computer Science","Risto Miikkulainen","Austin Waters"],"developers":["University of Texas at Austin researchers"],"harmed":["University students","University of Texas at Austin PhD applicants of marginalized groups","University applicants","Students","PhD applicants from underrepresented groups","PhD applicants","Educational communities","Computer science PhD applicants"],"report_count":2},{"incident_id":112,"occurred_on":"2012-10-09","title":"Police Departments Reported ShotSpotter as Unreliable and Wasteful","description":"ShotSpotter algorithmic systems locating gunshots were reported by police departments for containing high false positive rates and wasting police resources, prompting discontinuation.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"AI tangible harm event","sectors":["law enforcement"],"countries":["US"],"deployers":["Troy Police Department","Syracuse Police Department","San Francisco Police Department","San Antonio Police Department","New York City Police Department","Fall River Police Department","Chicago Police Department"],"developers":["ShotSpotter"],"harmed":["Troy residents","Troy Police Department","Syracuse residents","Syracuse Police Department","San Francisco residents","San Francisco Police Department","San Antonio residents","San Antonio Police Department"],"report_count":15},{"incident_id":433,"occurred_on":"2012-08-01","title":"Chicago Police's Strategic Subject List Reportedly Biased Along Racial Lines","description":"The Chicago Police Department reportedly used person-based predictive policing models, including the Strategic Subject List and Crime and Victimization Risk Model, to assign violence-risk scores to hundreds of thousands of residents. Official and media reports alleged that the program gave police a mathematically fragile basis for treating heavily policed residents as future victims or suspects, with Black Chicago residents especially exposed to the consequences of that scoring.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Chicago Police Department"],"developers":["Chicago Police Department"],"harmed":["Minority groups","General public of Chicago","General public","Economically vulnerable communities","communities of color","Black people","Black Chicago residents"],"report_count":9},{"incident_id":257,"occurred_on":"2012-05-04","title":"Police Reportedly Deployed ShotSpotter Sensors Disproportionately in Neighborhoods of Color","description":"Police departments disproportionately placed ShotSpotter sensors in black and brown neighborhoods, which is denounced by communities for allegedly creating dangerous situations, such as one involving in Adam Toledo's death.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Kansas City Police Department, Cleveland Division Of Police, Chicago Police Department, Atlanta Police Department"],"developers":["Shotspotter"],"harmed":["Neighborhoods Of Color, Brown Communities, Black Communities, Adam Toledo"],"report_count":4},{"incident_id":9,"occurred_on":"2012-02-25","title":"New York City Reportedly Released Disputed Value-Added Teacher Ratings for Thousands of Teachers","description":"After a legal dispute over public-records requests, the New York City Department of Education released Teacher Data Reports that used a value-added statistical model to rate thousands of public-school teachers based on estimated student test-score growth. News outlets published the ratings in February 2012, and teachers, unions, and analysts disputed the scores as imprecise and potentially misleading, citing large error margins, limited samples, and apparent roster-linkage errors.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":"none","sectors":["education"],"countries":["US"],"deployers":["New York City Department of Education"],"developers":["New York City Department of Education"],"harmed":["Teachers","Students","New York City teachers","New York City students","Epistemic integrity","Educational communities"],"report_count":6},{"incident_id":75,"occurred_on":"2012-01-05","title":"Google Instant's Allegedly 'Anti-Semitic' Results Lead To Lawsuit In France","description":"The organizations SOS Racisme, Union of Jewish Students of France, Movement Against Racism and for Friendship Among Peoples are suing Google due to its autocomplete software suggesting \"jewish\" when the names of certain public figures were searched on the platform.","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":["FR"],"deployers":["Google"],"developers":["Google"],"harmed":["Jewish People, Jewish Public Figures"],"report_count":1},{"incident_id":99,"occurred_on":"2012-01-01","title":"Major Universities Are Reportedly Using Race as a 'High Impact Predictor' of Student Success","description":"Several major universities are reportedly using a tool that uses race as one factor to predict student success.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Intentional","timing":"Post-deployment","harm_level":"none","sectors":["administrative and support service activities","education"],"countries":["US"],"deployers":["University of Wisconsin–Milwaukee","University of Massachusetts Amherst","University of Houston","Texas A&M University","more than 500 colleges","Georgia State University"],"developers":["EAB"],"harmed":["University students","Students","Latinx college students","indigenous students","Educational communities","Black college students"],"report_count":1}]}