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 & citationIncident 122: Examining an Instance of Unintended Bias in AI Systems
Read moreExploring Incident #116 in the AI Incident Database - A Case Study for Safe and Secure AI
Read moreAI Incident #111: Unintended Consequences in Predictive Modeling
Read moreAI Incident #112: Unintended Consequences of Auto-complete Function
Read moreAI Incident #113: Unintended Bias in Recommendation System
Read moreAI Incident #114: Unintended Prediction Bias Impact
Read moreExamining Incident #115: Unintended Consequences of AI Systems
Read moreAI Incident #118: Unintended Consequences in Recommender System
Read moreAI Incident #120: Unintended Consequences in Autonomous Vehicles
Read moreIncident Report #119: Unintended Consequences of AI Deployment
Read moreExploring Incident #164: An Examination of an AI Malfunction and Its Implications for Safe and Secure AI
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.