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

Examining an Incident of Biased AI (Racism): A Step Towards Trustworthy AI

Dive into this instance of AI bias, a prime example of the need for responsible AI governance. Understanding and addressing such incidents i...

Investigating the Electric Elves Incident: Ensuring Safe and Secure AI Operations

Dive into our in-depth analysis of the 'Electric Elves' incident, a case study that highlights the importance of responsible AI governance....

Robotic Surgery Complications: 144 Deaths Reported Since 2000 - Highlighting the Need for Safe and Secure AI

This AI incident involving robotic surgery maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The study reveal...

Google's Autocomplete Function Alteration Ordered by Japanese Court - Highlighting the Importance of Safe and Secure AI

In a significant development for Responsible AI governance, Google has been ordered to modify its autocomplete function in Japan. This incid...

Faulty Feature Causes Temporary Halt in Sales of Google's Nest Smart Smoke Alarm - An Incident Highlighting AI Governance in Safe and Secure AI

This incident involving Google's Nest Smart Smoke Alarm underscores the importance of AI governance in ensuring safe and secure AI applicati...

Examining LinkedIn's Response to Alleged Gender Bias in its AI Systems

Analyzing the approach taken by LinkedIn to address allegations of gender bias in their AI systems. This AI incident maps to the Govern func...

AI Mishap in New Zealand Passport Application Process: Highlighting the Importance of Responsible AI

An incident occurred in a New Zealand passport application process where an AI-powered robot, intended to assist applicants, instructed an i...

Potential Consequences of Inaccurate AI Deployments in Companies: A Guide to Responsible AI

Learn about the possible repercussions when a company's AI algorithms malfunction and understand how promoting trustworthy AI can help preve...

Unpacking the DAO Incident: Lessons for Responsible AI Governance

Explore the infamous DAO hack, its soft fork and hard fork aftermath, and how this incident maps to the Govern function in HISPI Project Cer...

The Tay Incident: A Pivotal Moment in AI Governance

Explore the infamous Tay incident, a bot that learned racist and offensive language from users on Twitter. This AI incident maps to the Gove...

Silicon Valley: Child Harmed by Unsafe AI Mall Security Robot - Emphasizing Need for Responsible AI

Recent incident involving a toddler being knocked down and run over by a mall security robot in Silicon Valley underscores the importance of...

Tesla Autopilot Incident: A Case Study for Responsible AI Harm Prevention

This tragic incident involving Joshua Brown, who lost his life in a self-driving car accident, underscores the importance of safe and secure...

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.