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

Unintended AI Termination: Understanding and Preventing Harm

Experiencing unexplained termination by an algorithm? This incident sheds light on the importance of responsible AI governance, emphasizing...

AI Malfunction in Chinese Bus Ad Highlights Importance of Safe and Secure AI

An AI malfunction in a Chinese bus ad has raised concerns about the need for responsible AI governance. This incident maps to the Govern fun...

Evaluating Hiring Algorithms for Bias: A Step Towards Responsible AI Harm Prevention

This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Auditors are testing hiring algorithms for...

Fatal Pedestrian Accident Involving Self-Driving Uber Vehicle Highlights Need for Responsible AI Governance

The recent self-driving Uber car accident in Arizona serves as a sobering reminder of the importance of safe and secure AI. This incident ma...

Elite: Dangerous AI Incident Highlights Need for Responsible AI Governance - Maps to HISPI Project Cerebellum Trusted AI Model (TAIM)

The recent incident in Elite: Dangerous, where the game's AI unintentionally developed superweapons, underscores the importance of safe and...

Deepfake AI-Generated Speech: A Case Study on Harm Prevention in AI

This deepfake incident involving a fake Obama speech highlights the importance of trustworthy AI. By understanding and addressing such incid...

AI Incident: Computer Program Erroneously Maintaining False Prisoner Detentions

This AI incident highlights the urgent need for responsible AI governance. The case illustrates an AI system incorrectly keeping prisoners i...

AI Incident: MIT Scientists Feed Violent Content to AI, Raising Concerns about Responsible AI Governance

This incident involving MIT scientists feeding violent content from Reddit to an AI highlights the importance of safe and secure AI governan...

National Residency Matching Program: A Case Study on AI Impact in the Labor Market

Exploring how AI is shaping the National Residency Matching Program, this analysis highlights the importance of responsible AI governance an...

Examining Racial Bias in AI Systems: A Case Study

This article delves into an incident highlighting racial bias in AI, underscoring the need for trustworthy AI practices. This AI incident ma...

Investigating the Mishap of Electric Elves: Ensuring Responsible AI Operations

Exploring the root causes behind the Electric Elves incident, highlighting the importance of safe and secure AI operations in preventing har...

Analysis Reveals Significant Incidents in Robotic Surgeries: 144 Fatalities Since 2000 - Emphasizing the Importance of Trustworthy AI Governance

This AI incident underscores the need for responsible AI governance and safe and secure systems, particularly in critical applications like...

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.