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

Racially Biased AI Incident in New Zealand: Passport Robot Suggests Applicant to Open Eyes

This discriminatory AI incident highlights the need for accountability and harm prevention in AI systems. The passport robot in New Zealand...

Preventing Harm from Incorrect AI Decisions: An Overview of Potential Consequences

Understanding the risks of misaligned AI decisions is crucial for fostering trustworthy and safe AI environments. This AI incident maps to t...

Exploring The DAO Incident: A Case Study in Responsible AI Governance

Delve into the infamous DAO hack, a significant event that underscores the importance of trustworthy and safe AI. This incident maps to the...

The Incident with Microsoft's AI Bot, Tay: A Case Study on AI Governance

Explore the infamous incident involving Microsoft's AI chatbot, Tay. This case study highlights the importance of responsible AI governance...

Silicon Valley Incident: AI-Powered Mall Security Robot Involved in Toddler Accident

An unfortunate incident occurred in Silicon Valley where an AI-powered mall security robot allegedly knocked down and ran over a toddler. Th...

Tesla Autopilot Failure: A Tragic Reminder of the Need for Responsible AI

The fatal accident involving Joshua Brown, who tragically lost his life in a self-driving Tesla, highlights the importance of trustworthy an...

Racial Bias Incident: Google's Image Search Results for Black Teenagers

Recent findings point to a racial bias in Google's image search results for black teenagers, highlighting the need for safe and secure AI an...

Understanding and Addressing Machine Bias in AI: A Key Component of Responsible AI

Explore the critical issue of machine bias in AI systems, a common challenge in AI governance. This AI incident maps to the Govern function...

Digital Assistant Malfunction Leads to Inappropriate Content: Harm Prevention in AI Governance

A recent incident involving a digital assistant inappropriately providing pornographic content to a child highlights the need for safe and s...

Incident Analysis: Amazon AI Misstep in Cell Phone Case Production – Emphasizing Safe & Responsible AI

This AI incident, involving Amazon's AI system in cell phone case production, underscores the need for trustworthy and responsible AI. The m...

Robodebt: Secret Documents Reveal Potential Flaws in AI Governance for Financial Assistance

This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The 'Robodebt' controversy highlights the...

Understanding the Yandex Chatbot Incident: A Case Study in Responsible AI

Explore the lessons learned from the Yandex chatbot incident, a relevant example demonstrating the importance of safe and secure AI. This AI...

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.