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 & citationExamining Racial Bias in Google Image Search Results: A Case of AI Incident
Read moreUnderstanding Potential Consequences of AI Malfunctions in Companies: A Guide for AI Governance
Read moreUnpacking the DAO Incident: A Case Study in AI Governance
Read moreThe Tay Incident: Understanding Harm Prevention in Responsible AI
Read moreSilicon Valley: A Case Study on the Importance of Safe and Secure AI - Mall Security Robot Accident
Read moreTesla Autopilot Incident Involving Joshua Brown: A Case for Responsible AI Governance
Read moreDigital Assistant Responds Inappropriately to Child's Request - Highlighting the Importance of Safe and Secure AI
Read moreRobodebt: Revealing the Algorithmic Flaws in Government Revenue Collection Systems - A Case for Responsible AI
Read moreInappropriate AI Output in Amazon's Mobile Accessory Production: An Unwanted Lesson on Responsible AI
Read moreBoeing's 737 Max 8 Incident: Understanding AI Safety and Leaking Abstractions
Read moreExamining Bias in Crime Prediction AI: A Case for Responsible AI and Harm Prevention
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.