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

NYPD's AI-powered Robo-dog Incident Demonstrates the Need for Responsible AI Governance

This incident involving the NYPD's robotic dog highlights the importance of safe and secure AI. The rapid response to public backlash unders...

Race as a Predictor in AI-Powered University Admissions Systems: An Unfair Bias?

In an alarming development, race is being used as a 'High Impact Predictor' in some university admissions systems powered by AI. This practi...

Understanding the 'Robo-Debt' Issue in French Welfare Services: A Case for Responsible AI

Exploring the recent 'robo-debt' issue in French welfare services, this article emphasizes the need for safe and secure AI in govern functio...

Discriminatory AI Allegedly Mistakes Thousands of Families for Fraudsters: A Case Study on the Importance of Responsible AI

Explore a recent AI incident involving discriminatory algorithms and its alarming consequences for innocent families. This AI incident maps...

Struggles of Personal Voice Assistants with Black Voices Highlighted in New Study: A Call for Responsible AI

A recent study reveals challenges faced by personal voice assistants when processing black voices, emphasizing the need for trustworthy and...

Bias in Twitter's Photo Crop Algorithm: White Faces and Women Preferred

An investigation into a concerning AI incident reveals that Twitter's photo crop algorithm favors white faces and women, potentially reinfor...

Examining California's Controversial Algorithm: The Impact on Vaccine Allocation and Responsible AI Governance

This AI incident in California's vaccine allocation algorithm highlights the need for transparency, fairness, and trustworthy AI practices....

Tesla's Controversial Claims on Autopilot Safety: A Review of AI Incidents

Exploring the debate surrounding Tesla's Autopilot system, this article reviews several incidents that question its safety claims. The discu...

South Korean Chatbot Incident Highlights Importance of Safe and Secure AI Practices

This AI incident underscores the need for trustworthy AI governance, emphasizing data privacy concerns in the tech industry. The chatbot's m...

Disturbing Huawei Patent for AI-Powered Uighur Detection Exposed: Ensuring Trustworthy AI

The recent surveillance group's exposure of a Huawei patent raises concerns about the use of AI for ethnic profiling. This incident maps to...

Misidentification Incident Highlights Importance of Responsible AI: Case Study on Black Teen at Skating Rink

A recent incident involving a black teen being kicked out of a skating rink after facial recognition misidentified her underscores the need...

Facial Recognition Site: Enforcing Trustworthy AI for Privacy and Safety

Explore the risks of misuse in facial recognition technology, highlighting a site that allows anyone to act as a cop or stalker. This AI inc...

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.