Apple Card Gender Bias Incident Highlights Importance of Trustworthy AI in Fintech
The latest gender bias complaints against Apple Card underscore the need for safe and secure, responsible AI in fintech. This AI incident ma...
Read moreValues Statement: We believe AI should cause no harm, but enhance the quality of human life, by proactively adopting our AI Governance framework.
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AI Incidents
Data source & citationFacebook Accused of Enabling Housing Discrimination by HUD - An Incident Highlighting the Need for Responsible AI Governance
The U.S. Department of Housing and Urban Development (HUD) has charged Facebook with enabling housing discrimination. This AI incident under...
Read moreCourt Ruling on Bias in Deliveroo's Algorithm Highlights Need for Responsible AI
The Italian court has ruled against Deliveroo's rider-ranking algorithm, which is perceived as discriminatory. This incident maps to the Gov...
Read morePause in Facial Analysis Use by Job Screening Service Highlights Need for Responsible AI Governance
Recent halt in the use of facial analysis by a job screening service underscores the importance of safe and secure AI. This AI incident maps...
Read moreLawsuit Over AI-Based Teacher Evaluations in Houston Schools: A Test for Responsible AI Governance
The ongoing lawsuit against the Houston Independent School District (HISD) over its use of AI in teacher evaluations presents an opportunity...
Read moreTesla Autopilot Misinterpreted Red Traffic Lights as Speed Limits: AI Incident Highlights Need for Safe and Secure AI
This Tesla Autopilot incident underscores the importance of responsible AI governance. The system mistook red traffic lights for speed limit...
Read moreAnalysis of N.Y.P.D. Robot Dog Incident: A Case Study for Responsible AI Governance
The incident involving the New York Police Department's robot dog serves as a critical reminder of the need for robust AI governance and tru...
Read moreRace Used as a Predictor in AI Models for Student Success at Major Universities - Harm Prevention and Safe AI
This AI incident, using race as a predictor of student success, underscores the need for trustworthy AI. Such practices can perpetuate biase...
Read moreExploring the Issue of 'Robo-Debt' in French Welfare Services: A Case for Responsible AI
This incident highlights potential pitfalls in AI applications, specifically in welfare services. The practice of generating 'robo-debt' cou...
Read moreThousands Affected by Discriminatory AI Allegations: An Incident Highlighting the Need for Responsible AI Governance
Learn about a recent incident involving a discriminatory algorithm, wrongly accusing thousands of families of fraud. This AI incident maps t...
Read moreStruggles of Personal Voice Assistants with Black Voices Highlighted in a Recent Study - Mapping to the Govern Function within HISPI Project Cerebellum Trusted AI Model
A recent study reveals challenges faced by personal voice assistants when interacting with black voices. This underscores the importance of...
Read moreBias in Twitter's Photo Crop Algorithm: Focus on White Faces and Women
Exploring the unintended consequences of AI algorithms, this incident highlights the importance of trustworthy AI governance in ensuring saf...
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.