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

Exploring Limitations in AI: A Case Study on the Latest Turing Test

This article sheds light on a recent Turing Test, revealing important lessons about AI limitations. Understanding these shortcomings is cruc...

Waze and Los Angeles Wildfires: Ensuring Responsible AI for Harm Prevention

Exploring Waze's approach to navigating LA wildfires, this incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model...

Analyzing a Self-Driving Shuttle Accident: A Lesson in Responsible AI and Safe & Secure AI Operations

This AI incident involving a self-driving shuttle offers valuable insights into the importance of trustworthy AI, especially in operational...

Unforeseen Consequence: Robot Injures Worker at Volkswagen Plant – A Reminder for Safe and Secure AI Governance

A recent incident involving a robot killing a man at a Volkswagen plant in Germany serves as a grim reminder of the importance of responsibl...

California Autonomous Vehicle Incident Involving Google and Delphi Self-Driving Cars - Advancing Responsible AI Governance

This autonomous vehicle incident in California involving both Google and Delphi self-driving cars raises important questions about the need...

Apple's Face ID bypassed: A closer look at AI security safeguards

Recent incident reveals potential vulnerabilities in Apple's Face ID system, underscoring the importance of trustworthy AI and robust govern...

Avertive of Global Nuclear Disaster: The Role of Stanislav Petrov (1983) - An Instance of Safe and Secure AI

In 1983, Soviet officer Stanislav Petrov made a crucial decision that potentially averted a global nuclear disaster. This AI incident highli...

Boeing 737 Max 8 Incident: An Example of AI Safety and Leaking Abstractions

Investigate the tragic Boeing 737 Max 8 incident, a stark reminder of the importance of AI safety and addressing leaking abstractions. This...

Understanding the Role of AI in the 2010 'Flash Crash': A Case Study for Responsible AI Governance

Dive into this detailed analysis of an AI incident that impacted the global market in 2010, highlighting the importance of safe and secure A...

Debunking the Myth: The Neural Net Tank Urban Legend – A Reminder of Safe AI Practices

Exploring the Neural Net Tank urban legend sheds light on potential pitfalls in AI development. This AI incident maps to the Govern function...

Unsafe Autonomous Driving Incident: Tesla's Challenge for Responsible AI Governance

This autonomous driving incident involving a Tesla vehicle highlights the need for trustworthy AI governance. The incident maps to the Gover...

Driverless Delhi Metro Train Crash: A Case Study on the Importance of Safe and Secure AI

Incident analysis of a driverless train crash on the Magenta line, highlighting the need for robust AI governance and harm prevention mechan...

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.