Target didn’t figure out a teen girl was pregnant before her father did
A 15-year-old girl in the UK was mistakenly labeled as 'female' by Target's AI system, despite being pregnant. The system failed to detect h...
Read moreEvidence-based Transparent For governance
A 15-year-old girl in the UK was mistakenly labeled as 'female' by Target's AI system, despite being pregnant. The system failed to detect h...
Read moreAn AI-powered traffic camera mistakenly identified a pedestrian's shirt as a license plate, leading to a fine for the driver in question. Th...
Read moreExploring the instance where AI misdiagnosed a patient's rare condition, causing unnecessary suffering. Emphasizing the need for responsible...
Read moreExploring the challenges faced by hundreds of AI tools designed to aid in COVID-19 detection, and the lessons learned for building responsib...
Read moreA new wave of deepfake technology is challenging the authenticity of online profiles, particularly on LinkedIn. This development underscores...
Read moreIn an unusual incident, a self-driving taxi from General Motors' Cruise autonomous fleet was pulled over by the police in San Francisco. The...
Read moreExplore the intricacies surrounding a recent incident involving a driverless Cruise vehicle being pulled over by law enforcement. The event...
Read moreRecent legal actions taken by the company Proctorio, known for their AI-powered online proctoring services, have raised concerns over respon...
Read moreIn a significant step towards responsible AI governance, Erik Johnson, an Electronic Frontier Foundation (EFF) client, has settled his lawsu...
Read moreExploring the lessons learned from incident #29, we delve into the challenges posed by unforeseen consequences in AI systems. This case stud...
Read moreRecent events surrounding the deployment of an autonomous driving application, Incident #103, have raised serious concerns about the safety...
Read moreRecent findings from Incident #104 reveal a concerning instance of unintended bias within an AI-powered recommendation system, which negativ...
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.