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 & citationTesla Autopilot Incident: A Case Study for Responsible AI Governance
Read moreExamining Google's Image Search Bias Incident: A Step Towards Responsible AI Governance
Read moreAddressing Machine Bias in AI Systems: A Responsible Approach
Read moreInappropriate Content Incident: Digital Assistant Responds with Porn to Children's Request
Read moreIncident Analysis: Amazon AI's Misstep in Cell Phone Case Production - A Case Study for Safe and Secure AI
Read moreUnveiling the Robodebt Saga: Secrets That Showcase AI Governance Failures
Read moreUnderstanding the Role of Responsible AI in the Yandex Chatbot Incident - Learn from Project Cerebellum's AI Incident Database
Read moreGoogle Translate's Error: Female Historians and Male Nurses Non-existent to European Users - A Reminder for Responsible AI
Read moreApology from FaceApp over Controversial Skin-Toning Filter: A Case Study for Responsible AI
Read moreAI Bots on Wikipedia Dive into Edit Wars: A Case Study in Responsible AI
Read moreLessons from Kaggle's Fisheries Competition: Promoting Responsible AI in Marine Stewardship
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.