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 & citationAnalyzing the COMPAS Recidivism Algorithm: A Step Towards Trustworthy AI
Read moreControversial AI Software Company Shifts Towards Responsible AI: Moves Align with Trustworthy AI Model
Read moreYouTube Videos Deceiving Children: A Call for Responsible AI and Safe Content
Read moreUnbearable Pain: The Case of AI Bias in Healthcare Decisions
Read moreMisidentification Incident: AI Mistakes Pedestrian's Shirt for License Plate
Read moreTeen Girl's Pregnancy Unnoticed by AI Target System Until Father Discovered
Read moreFacebook Sued Over $150 Billion for Alleged Role in Rohingya Violence: A Case Study in AI Governance
Read moreAddressing Popularity Bias in AI-Powered Media Recommendation Systems: A Step towards Trustworthy AI
Read moreExploring Tesla Autopilot's Security: An Experiment by Tencent Keen Security Lab - Implications for Safe and Secure AI
Read moreFacebook Ad Delivery: Unintended Discrimination and the Importance of Responsible AI Governance
Read moreInappropriate Response from Amazon Alexa: Ensuring Responsible AI Use in Kids' Devices
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.