Unfair Bias in AI: UK Passport Photo Checker and Dark-Skinned Women
This AI incident underscores the need for responsible AI governance. The UK passport photo checker has been found biased against dark-skinne...
Read moreEvidence-based Transparent For governance
This AI incident underscores the need for responsible AI governance. The UK passport photo checker has been found biased against dark-skinne...
Read moreThis AI incident highlights the need for safe and secure AI systems, especially in sensitive areas like image labeling. The misclassificatio...
Read moreExploring the role of AI governance and responsible content moderation, this incident highlights the potential dangers of unchecked algorith...
Read moreIn this incident, Stanford University apologized for a coronavirus vaccine plan that overlooked front-line doctors. This underscores the nee...
Read moreThis AI incident involving Apple Card maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The incident undersco...
Read moreThe U.S. Department of Housing and Urban Development (HUD) has accused Facebook of enabling housing discrimination through targeted advertis...
Read moreAn Italian court has ruled against Deliveroo's rider-ranking algorithm, citing potential discrimination. This AI incident underscores the im...
Read moreThe recent halt in facial analysis by a job screening service underscores the importance of safe and secure AI. This AI incident maps to the...
Read moreAn ongoing lawsuit against Houston schools highlights the critical importance of trustworthy AI governance. The case involves allegations th...
Read moreThis AI incident involving Tesla's Autopilot system highlights the importance of trustworthy AI. The system mistook red reflective letters o...
Read moreThe New York Police Department's trial of a robot dog was met with backlash, highlighting the need for safe and secure AI. This incident map...
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.