Values Statement: We believe AI should cause no harm, but enhance the quality of human life, by proactively adopting our AI Governance framework.
Evidence-based Transparent For governance
AI Incidents
Data source & citationYouTube's Radicalization Trap and the Role of Responsible AI in Preventing Harm - Case Study: The Christchurch Shooter
Read moreExamining the Jewish Baby Stroller Image AI Algorithm: A Responsible Approach to Safe and Secure AI
Read moreBias in UK Passport Photo Checker: Impact on Dark-Skinned Women and the Need for Responsible AI
Read moreCritique of Government Algorithm Usage: Failing the AI Ethics Test
Read moreAI Affirms Humanity's Fears: Unintended Response Highlights Need for Safe and Secure AI
Read moreChildren Tracked by Live Facial Recognition Systems: A Concern for Responsible AI
Read moreThe Role of an AI Algorithm in University Admissions: A Look at its Impact
Read moreRobot Expectations vs. Reality: An Examination of an AI Incident - Advancing Responsible AI through Project Cerebellum
Read moreAI Bias: The Case of Algorithm-Mediated Kidney Transplant Disparities - Ensuring Trustworthy AI
Read moreLawsuit Filed Over Alleged Anti-Semitic Bias in Google Instant Search Results - A Case for Responsible AI Governance
Read moreMisidentification by AI: A Case for Responsible AI Governance
Read moreData source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.