Values 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

AI Lesson from the 1983 Nuclear Incident: The Vital Role of Human Judgement in AI Governance

In 1983, Stanislav Petrov's human judgement averted a global nuclear disaster. This AI incident maps to the Govern function in HISPI Project...

Boeing 737 Max 8 AI Incident: An Example of the Importance of Leak-Proof Abstractions in Responsible AI

This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The Boeing 737 Max 8 disaster illustrates...

Flash Crash of 2010: Role of AI in High-Frequency Trading Under Scrutiny

The recent arrest of a UK speed trader sheds light on the 2010 'flash crash'. This incident maps to the Govern function in HISPI Project Cer...

Debunking the Myth: The Impact of Neural Net Tanks on AI

Unveiling the truth behind the Neural Net Tank Urban Legend, this article explores its implications for AI governance and responsible AI dev...

Unforeseen Consequences in Autonomous Driving Systems: The Case of Tesla Incident

This AI incident involving a self-driving Tesla vehicle highlights the importance of responsible AI governance and trustworthy autonomous dr...

Driverless Delhi Metro Train Crash: Harm Prevention in AI Incidents - Mapping to Govern Function in Project Cerebellum

A recent accident on the Magenta line of Delhi Metro has raised concerns about AI governance and safety. This incident maps to the 'Govern'...

AI Facial Recognition Incident in China: iPhone X Unlocked by Co-worker's Face

An AI facial recognition incident occurred in China where a colleague was able to unlock an iPhone X using his face, raising concerns about...

Unauthorized Use of Alexa Leads to Home Raided - An Important Lesson in AI Governance

This AI incident highlights the need for trustworthy AI and responsible use of voice assistants like Alexa. The misuse of such technology ca...

Potential Mechanism Behind Amazon Echo Commercial-Detection System: A Step Towards Responsible AI

This AI incident sheds light on Amazon's commercial-detection mechanism for Echo devices, a crucial aspect of safe and secure AI. This mecha...

Unintended Termination: A Case Study in AI Incident Analysis – Powered by Project Cerebellum's Trustworthy AI Model

An employee was unexpectedly dismissed by an algorithm, prompting a thorough investigation that remains inconclusive. This AI incident maps...

Unintended Face Matching Incident Highlights Need for Responsible AI Governance

A recent incident involving Chinese AI misidentifying a passenger in a bus ad showcases the importance of trustworthy AI and safe and secure...

Examining Amazon's Recruiting Algorithm: A Case Study of Gender Bias in AI

This article explores the controversial recruiting algorithm used by Amazon, shedding light on the potential for gender bias in AI systems....

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.