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 & citationEvaluating Hiring Algorithms for Bias: A Step Towards Responsible AI and Harm Prevention
Read moreChina Woman Claims Co-worker's Face Could Unlock iPhone X - Implications for Trustworthy AI
Read moreUnauthorized Use of Alexa for Emergency Situations: A Case Study on Responsible AI Governance
Read moreUncovering Amazon's Strategy for Silencing Alexa During Commercials - A Look into AI Incident Database
Read moreExploring Unintended Consequences in AI Systems: A Case Study
Read moreUnintended Consequence: Chinese AI Misidentification in Bus Advertisement
Read moreAnalyzing the Impact of Deepfakes: A Case Study on a Fake Obama Speech Created Using AI
Read moreExamining an AI Incident: The Impact of Violent Content on MIT's Experiment - Promoting Safe and Secure AI
Read moreArtificial Intelligence Bias Leads to Wrongful Convictions: A Case Study
Read moreDelhi Metro Accident Highlights Need for Safe and Secure AI: Driverless Train Crashes Through Wall
Read moreElite: Dangerous AI Superweapon Incident Highlights Importance of 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.