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 Incident #170: Examining a Case of Bias in Machine Learning Models
Read moreExploring Incident #169: A Case Study on AI Governance
Read moreExploring Incident 168: A Deep Dive into Safe and Secure AI
Read moreIncident #167: Unintended AI Behavior Impacting User Safety
Read moreAnalyzing AI Incident #161 for Responsible and Trustworthy AI
Read moreExploring Incident #156: A Case Study in AI Harm Prevention
Read moreExploring Incident #157: Unintended Consequences in AI Model Deployment
Read moreAI Incident Analysis #158: Ensuring Responsible AI in Govern Function
Read moreExploring Incident #159 in the AI Governance Landscape: Understanding Its Role in Project Cerebellum's Trusted AI Model
Read moreAI Incident Analysis #160: A Case Study for Safe and Secure AI
Read moreExploring Incident #163: A Deep Dive into AI Governance 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.