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 Overhyped AI Claims in Medicine: Promoting Responsible Healthcare AI
Read moreRacial Bias in Healthcare AI: Case Study on a Predictive Algorithm
Read moreCalifornia Legislation Targets Warehouse AI: A Step Forward for Responsible AI Governance
Read moreUnintended Robot Collision Triggers Fire: A Case Study on Safe and Secure AI
Read moreMicrosoft Replaces Human Journalists with AI: A Case Study for Responsible AI Transition
Read moreEthical Guardrails Implemented by Tech Companies for Responsible AI Deployment
Read moreMass Shooting Videos Confused with Car Washes by Facebook AI Moderator: Understanding AI Incidents and the Importance of Responsible AI Governance
Read moreEthnicity Detection Algorithm Incident at Alibaba Cloud: A Case for Responsible AI
Read moreFlagging Cheating in California Bar Exam: Importance of Responsible AI for Harm Prevention
Read moreTikTok Anorexia Videos Evade 'Pro-Ana' Ban via Misspelled Hashtags: A Case Study in AI Harm Prevention
Read moreAccount Deletion of a Latinx Transgender Woman on TikTok Highlights Need for AI Bias Awareness
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.