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

TAIM catalog Map Data source & citation Failure Files™

Incident #109

This article delves into an instance (Incident #109) where a misconfigured autonomous vehicle's navigation system led to an accident, underl...

Incident #110

This article delves into Incident #110, an instance where the lack of robust safety measures in an AI model led to unexpected outcomes. The...

Incident #111

Recently, an incident was reported involving a healthcare AI system demonstrating potential bias towards certain patient demographics. This...

Incident #112

An incident involving a machine learning model developed for predicting loan eligibility demonstrated unintended bias, resulting in unfavora...

Incident #113

This article delves into an incident involving a data breach in an AI system, highlighting the importance of robust security measures and re...

Incident #114

This article delves into a recent instance of an AI system's unforeseen consequences during deployment. The incident underscores the need fo...

Incident #115

Recently, an AI-powered recommendation system used by a popular e-commerce platform displayed biased results, showing fewer products from un...

Incident #116

In this exploration, we delve into a real-life incident involving an autonomous vehicle's miscalculation in a busy intersection. The AI mode...

Incident #117

Incident #117 underscores the need for robust governance in ensuring safe and secure AI development. This incident, involving a self-driving...

Incident #118

Last week, an unexpected event occurred in AI System #118 developed by XYZ Tech. The incident highlighted the importance of responsible AI g...

Incident #119

Incident #119 sheds light on a critical lapse in Responsible AI governance, demonstrating the need for robust safeguards in our artificial i...

Incident #120

Recent events have highlighted an unforeseen issue involving AI System #120, developed by a leading tech company. The system, designed to st...

Data 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.