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 & citationTeachers Launch Widespread Appeals Against Biased AI Evaluation Systems - Highlighting the Need for Responsible AI Governance
Read moreTeaneck NJ Bans Use of Biased Facial Recognition Technology by Police – A Step Towards Trustworthy AI
Read moreLawsuit Over Alleged Anti-Semitic Google Instant Results Highlights Need for Safe and Secure AI
Read moreTracking Minors Suspected of Criminal Activity: A Concern in Live Facial Recognition Systems - The Need for Responsible AI Governance
Read morePolice Robot's Response to Crime Report: A Remarkable AI Incident
Read moreExploring the Hidden AI Decision-Making Impacting College Admission
Read moreAlgorithm Bias: The Discrimination Against Black Patients in Kidney Transplant Decisions
Read moreFootball Match Disrupted by AI Misidentifying Ref's Bald Head: An Example of AI Mistakes and the Need for Responsible AI Governance
Read moreUncovering Bias in Chest X-Ray AI Classifiers: A Call for Responsible AI Governance
Read moreFacebook's Response to the Lekki Massacre Incident: A Look at False Information Governance
Read moreExploring Controversies in Spam Filter AI: A Look Beyond Efficiency
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.