{"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":239,"occurred_on":"2009-09-01","title":"Algorithmic Teacher Evaluation Program Reportedly Failed to Improve Student Outcomes and Was Alleged to Have Harmed Teachers","description":"Gates Foundation-funded Intensive Partnerships for Effective Teaching Initiative's algorithmic program to assess teacher performance reportedly failed to achieve its goals for student outcomes, particularly for minority students, and was criticized for potentially causing harm against teachers.","mit_domain":"AI system safety, failures, and limitations","mit_subdomain":"Lack of capability or robustness","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":"unclear","sectors":["education"],"countries":["US"],"deployers":["Intensive Partnerships for Effective Teaching"],"developers":["Intensive Partnerships for Effective Teaching"],"harmed":["Teachers","Students","Minority students","Minority groups","Epistemic integrity","Educational communities","Economically vulnerable students","Economically vulnerable people"],"report_count":1},{"incident_id":245,"occurred_on":"2009-03-30","title":"Unverified Misreading by Automated Plate Reader Led to Traffic Stop and Restraint of an Innocent Person at Gunpoint in California","description":"In San Francisco, an automated license plate reader (ALPR) camera misread a number as belonging to a stolen vehicle having the wrong make, but its photo was not visually confirmed by the police due to poor quality and allegedly despite multiple chances prior to making a traffic stop, causing an innocent person to be pulled over at gunpoint and restrained in handcuffed.","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":["San Francisco Police Department"],"developers":["Unknown"],"harmed":["Denise Green"],"report_count":1}]}