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 & citationExamining California's Equity Algorithm Impact on Vaccine Allocation: Harm Prevention in AI Governance
Read moreExploring Bias in AI Image Cropping: The Case of Twitter's Algorithm
Read moreAddressing Racial Bias in Automated Speech Recognition: A Step Towards Trustworthy AI
Read moreResponsible AI in Education: Addressing Teacher Evaluation Lawsuit at Houston Schools
Read moreApology for Exclusion in COVID-19 Vaccine Plan Highlights Importance of Responsible AI Governance
Read moreGender Bias Allegations Highlight the Importance of Responsible AI in Financial Services: Apple Card Case Study
Read moreFacebook Allegedly Violating Fair Housing Laws through AI Practices: A Case for Responsible AI Governance
Read moreCourt Ruling Against Discriminatory AI in Deliveroo Algorithm: A Step Towards Responsible AI Governance
Read morePause in Job Screening Service's Facial Analysis of Applicants: An Instance of AI Harm Prevention
Read moreNYPD's AI-Powered Robot Dog Incident Highlights Need for Responsible AI Governance
Read moreExploring 'Robo-Debt' in French Welfare Services: A Case Study on AI Incident 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.