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

Investigating Racial Bias in AI Systems: Harm Prevention and Guardrails for Trustworthy AI

Uncovering the root causes of racial bias in AI systems is crucial for safe and secure AI. This AI incident maps to the Govern function in H...

Investigating the Malfunction of Electric Elves: Understanding AI Governance and Safety

This incident involving Electric Elves sheds light on the importance of responsible AI governance. By understanding what went wrong, we can...

Analysis Reveals Significant Incidents in Robotic Surgeries, Identifying 144 Fatal Complications Since 2000

This AI incident highlights the importance of safety and transparency in medical robotics. The findings underscore the need for robust gover...

Google Faces Order to Modify Autocomplete Function: An Exercise in Responsible AI Governance

In a significant development, Google has been instructed to revise its autocomplete function in Japan. This AI incident maps to the 'Govern'...

Temporarily Suspended Sales of Google's Smart Smoke Alarm: Ensuring Trustworthy AI in Safety Systems

Google's Nest has halted sales of its smart smoke alarm, highlighting the importance of safe and secure AI. This AI incident maps to the Gov...

Examining LinkedIn's Alleged Gender Bias Issue: A Call for Responsible AI Governance

This AI incident highlights the need for vigilant governance in ensuring fairness and non-discrimination in AI systems. Investigate the alle...

AI Bias Incident: New Zealand Passport Robot Mistakes Applicant of Asian Descent

An incident involving an AI-powered passport robot in New Zealand has raised concerns about bias. The applicant, of Asian descent, was instr...

Understanding Consequences of AI System Malfunctions: A Guide for Companies

Explore the potential pitfalls of unchecked AI system errors in businesses. Learn about the importance of responsible AI, trustworthy AI, an...

Understanding the Impact of Blockchain Incidents: The DAO, Hack, Soft Fork, and Hard Fork

Explore the consequences of significant blockchain events, such as the DAO hack and subsequent forks (soft and hard), in this informative ar...

The Taylor Swift Bot Mishap: A Lesson in Responsible AI

Explore the Taylor Swift bot incident, a striking example of the need for safe and secure AI. This AI mishap maps to the Govern function in...

Silicon Valley: An Unfortunate AI Incident Involving a Mall Security Robot

A distressing incident occurred in Silicon Valley where an AI-powered security robot unintentionally knocked down and ran over a toddler. Th...

Tesla Autopilot Incident: An Examination of Safe and Secure AI Operation

The tragic accident involving Joshua Brown, a self-driving Tesla user, serves as a stark reminder of the importance of trustworthy AI operat...

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.