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

Lessons from Kaggle's Fisheries Competition: AI Harm Prevention and Governance

Explore the insights gained from the Kaggle fisheries competition, demonstrating the importance of responsible AI governance for safe and se...

Improving AI's Performance in Writing Christmas Carols: A Case Study

Explore the challenges faced by AI in creating Christmas carols, a task demonstrating the need for safe and secure AI. This AI incident maps...

Responsible AI in Action: Google Photos AI Incident Analysis

This AI incident involving Google Photos demonstrates the importance of trustworthy AI. The AI misinterpreted a ski photo, highlighting the...

Robot Employee Causes Unintended Customer Fear: An Illustration of AI Incident Harm Prevention

This incident involving a robot employed to assist customers illustrates the importance of safe and secure AI operation. The robot's actions...

Flawed AI Reward Systems in Real-World Applications: Harm Prevention and Guardrails for Safe and Secure AI

Incident analysis reveals the impact of faulty reward functions in AI systems, underlining the importance of trustworthy AI governance. This...

Uber's Self-Driving Car Violates Traffic Law, Highlighting Need for Responsible AI Governance

Incident: Uber's self-driving car running a red light underscores the critical importance of trustworthy AI and effective AI governance. Thi...

Unpatriotic Messages by China's AI Chatbots Lead to Disciplinary Action: A Look into Harm Prevention in AI Governance

This incident involving unpatriotic messages sent by AI chatbots in China highlights the need for responsible and trustworthy AI. It maps to...

Autopilot Failure Leads to Dangerous Incident: Highlighting the Importance of Safe and Secure AI Governance

A recent incident involving a Tesla driver under the influence raises concerns about the reliability and safety of Autopilot. This AI incide...

AI Incident: Security Robot Malfunctions Near Water Source

An incident involving a security robot occurred when the autonomous machine malfunctioned near a water fountain, causing it to enter the wat...

AI System Malfunction Results in Tragic Incident at Haryana's Manesar Factory - Understanding the Govern Function in Project Cerebellum's Trusted AI Model

Explore this incident involving an AI system malfunction that led to a tragic accident in a Haryana factory. This AI incident maps to the Go...

Snow Blindness in Self-Driving Cars: An Incident Highlighting the Need for Safe and Secure AI

This incident involving self-driving cars demonstrates the importance of robust and adaptable AI systems. The issue, known as 'snow blindnes...

Responsible AI Incident: Google Self-Driving Car Collision - Highlighting the Need for Safe and Secure AI

A self-driving car developed by Google was involved in a collision after another vehicle jumped a red light. This AI incident underscores th...

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.