{"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":469,"occurred_on":"2006-02-25","title":"Automated Adult Content Detection Tools Showed Bias against Women Bodies","description":"Automated content moderation tools to detect sexual explicitness or \"raciness\" reportedly exhibited bias against women bodies, resulting in suppression of reach despite not breaking platform policies.","mit_domain":"Discrimination and Toxicity","mit_subdomain":"Unfair discrimination and misrepresentation","entity":"AI","intent":"Unintentional","timing":"Post-deployment","harm_level":null,"sectors":[],"countries":[],"deployers":["Meta, Linkedin, Instagram, Facebook"],"developers":["Microsoft, Google, Amazon"],"harmed":["Linkedin Users, Instagram Users, Facebook Users"],"report_count":3}]}