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 & citationMeta Accused of Deceiving Public Regarding Impact of Products on Children's Wellbeing: A Case for Safe and Secure AI
Read moreHow a Flawed AI English Test Affected Thousands - Understanding AI Incidents and Their Role in Trustworthy AI
Read moreFacebook Ad Delivery Bias: An Examination of Skewed Outcomes and the Importance of Responsible AI
Read moreSuspicious Response from Alexa: A Case Study in AI Incident and Responsible AI Governance
Read moreExperimental Analysis on AI-Driven Autonomous Vehicles: A Case Study of Tesla Autopilot and Its Implications for Safe and Secure AI
Read moreExploring Amaya's Flashlight Incident: A Case Study on AI Governance
Read moreExploring Liability in AI-Assisted Driving: The Amazon Delivery Driver Crash Case
Read moreExploring Amazon's Algorithmic Suggestions Linked to Suicide Attempts: A Case for Responsible AI
Read moreMisleading Google Maps Directions During Snowstorm: A Case Study of Safe and Secure AI
Read moreIssues found in an AI tool supporting federal low-risk prisoner early release: Promoting safe and secure AI
Read moreAI Misinterpretation: Moon Mistaken for a Yellow Stop Light
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.