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

Learnings from Kaggle's Fisheries Competition: Promoting Safe and Secure AI

Explore insights gained from the fisheries competition on Kaggle, shedding light on responsible AI practices in data prediction and harm pre...

The Challenges in Developing Trustworthy AI for Music Generation: The Case of Christmas Carols

This AI incident highlights the complexities involved in creating safe and secure AI, particularly when it comes to music generation. Despit...

Analyzing Google Photos' Attempt at Correcting a Ski Photo - A Case Study in Responsible AI

This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The Google Photos application attempted an...

Robot Employee Causes Customer Deterrence Incident at Local Store: Lessons in Responsible AI

An unfortunate AI incident unfolded when a store hired a robot to assist customers, instead causing them distress. This AI incident undersco...

Unsafe AI Incident: Faulty Reward Functions in the Wild - Harm Prevention through Responsible AI Governance

This incident highlights the importance of safe and secure AI, particularly in the area of reward functions. The malfunction can lead to und...

Self-Driving Uber Vehicle Violates Traffic Regulations: A Case for Responsible AI Governance

This AI incident involving a self-driving Uber vehicle running a red light underscores the importance of safe and secure AI. It maps to the...

Unpatriotic Messages from Chinese Chatbots: An Incident Illustrating the Need for Responsible AI Governance

This AI incident involving Chinese chatbots disseminating unpatriotic messages underscores the importance of trustworthy and safe AI. It map...

Tesla Autopilot Incident: Highlighting the Importance of Responsible AI Governance

This Tesla incident underscores the need for trustworthy AI, emphasizing the role of AI governance in ensuring safe and secure autonomous ve...

AI Incident: Robot Security Guard Malfunction Leads to Unintended Drowning

In an unfortunate incident, a robot security guard malfunctioned, leading to it entering a water fountain and drowning itself. This AI incid...

Human Tragedy in Manesar Factory: AI System Malfunction Leads to Fatality

Incident at Haryana's Manesar factory highlights the need for responsible AI governance. A robot malfunction resulted in a tragic loss of li...

Snow Blindness in Self-Driving Cars: A Case Study in Safe and Secure AI

Incident involving autonomous vehicles suffering from 'snow blindness' highlights the need for responsible AI governance, emphasizing the im...

Responsible AI Incident: Google Self-Driving Car Collision After Other Vehicle Jumped Red Light - Harm Prevention in AI

This AI incident involving a Google self-driving car collision demonstrates the importance of safe and secure AI. When another vehicle jumpe...

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.