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 & citationFacial Recognition Ban in Teaneck NJ Highlights Importance of Responsible AI Governance
Read moreLawsuit Over Google Instant's Alleged Anti-Semitic Search Results Highlights Importance of Responsible AI Governance
Read moreTracking Children Suspected of Criminal Activity Using Live Facial Recognition: A Case Study on AI Incident Harm Prevention
Read moreAI-powered police robot's unexpected behavior: Singing instead of responding to crime report
Read moreExploring the Role of AI in University Admissions: A Look at a Recent Incident
Read moreAlgorithm Bias Exposure: The Case of Blocked Kidney Transplants for Black Patients - Highlighting the Importance of Responsible AI
Read moreHumorous Incident Highlights Need for Responsible AI: Football vs Referee's Head
Read moreUnveiling Bias in Chest X-Ray Classifiers: A Call for Trustworthy AI
Read moreThe Lekki Massacre: Understanding Facebook's 'False' Content Label and the Importance of Safe and Secure AI
Read moreReevaluating Spam Filters: A Look at AI's Unnoticed Controversy
Read moreFacebook Fails to Detect Misinformation on COVID-19 and Voting: A Call for Responsible AI
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.