AI-controlled police robot misbehaves, sings instead of assisting
An incident involving an AI-controlled police robot has raised concerns about the responsible use of artificial intelligence in public safet...
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
TAIM catalog Map Data source & citationStanford's Initial Vaccine Distribution: Prioritizing Seven Medical Residents
Exploring the initial vaccine distribution strategy at Stanford University, where only seven doses were designated for medical residents amo...
Read moreGoldman Sachs' Apple Card Algorithm under Scrutiny over Perceived Gender Bias
A recent study has raised concerns about potential gender bias in the algorithm used for Apple Card, issued by Goldman Sachs. The research s...
Read moreExamining Gender Bias in Apple Card: A Crucial Look at Fintech Responsibility
Recent complaints about gender bias in the approval process of Apple Card highlight an urgent need for responsible AI governance in the fint...
Read moreChallenging Inaccurate Facial Recognition Matches: A Case of False Alarm in Detroit
A man falsely identified by facial recognition technology used by Detroit Police Department is suing the department. The incident raises con...
Read moreThousands Mistakenly Accused by Biased AI System: A Case for Responsible AI Governance
Recent incidents highlight the potential harm of discriminatory algorithms, as thousands of families were falsely accused of fraud. This und...
Read moreTwitter's Photo Crop Algorithm Bias Towards White Faces and Women: An Examination of Responsible AI
A recent study revealed that Twitter's photo crop algorithm appears to favor white faces and women, raising concerns about safe and secure A...
Read moreCalifornia's Equity-Focused Algorithm and Potential Unintended Consequences for Vulnerable Populations
A California algorithm aimed at prioritizing vaccine distribution to underserved communities may inadvertently exclude up to 2 million vulne...
Read moreBalancing Safety: Tesla's Autopilot vs User Experience
In the ongoing debate over Autopilot, Tesla asserts its self-driving technology enhances safety while critics contend it may pose risks. Thi...
Read moreLegal Dispute Surrounding Data Collection in AI Chatbot: The Need for Responsible AI Governance
A high-profile legal dispute has erupted over an AI chatbot, casting a shadow on the data collection practices within the AI sector. This in...
Read moreHuawei's Controversial Patent for AI-Powered Uighur Detection Exposed
A surveillance group has uncovered a patent filed by Huawei that details an AI system designed to identify members of the Uighur ethnic mino...
Read moreRoller Rink Denies Access to Teen Due to Incorrect AI Identification as Banned Individual
An unfortunate incident occurred at a roller rink, where a teenage girl was refused entry due to an error in the AI system. The AI incorrect...
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.