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 & citationAI Stated It Cannot Avoid Potential Harm to Humankind - Highlighting the Need for Responsible AI
Read moreGovernment's Algorithm Performance: A Poor Grade - Exploring Responsible AI in Policy Making
Read moreExamining Bias in AI: The Case of the UK Passport Photo Checker — A Call for Responsible AI Governance
Read moreAI Incident: Jewish Baby Stroller Misclassification - Highlighting the Need for Responsible AI
Read moreDisturbing AI-Powered Uighur Detection Patent Exposed by Surveillance Group: Highlighting the Need for Responsible AI Governance
Read moreAddressing Racial Bias in Automated Speech Recognition: A Step Towards Trustworthy AI
Read moreExploring Bias in AI Image Cropping: The Case of Twitter's Algorithm
Read moreExamining California's Equity Algorithm Impact on Vaccine Allocation: Harm Prevention in AI Governance
Read moreAssessing the Safety of Tesla's Autopilot: A Clash between Promised Security and Real-world Incidents
Read moreSouth Korean Chatbot Incident Highlights Importance of Responsible AI in User Data Handling
Read moreFacial Recognition Site Highlights Need for Responsible AI Governance - Incident Maps to HISPI Project Cerebellum Trusted AI Model (TAIM)
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.