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

Lawsuit Over Teacher Evaluation System in Houston Schools: A Case Study on AI Accountability

An ongoing lawsuit highlights the need for responsible AI governance in educational settings. The case revolves around a teacher evaluation...

Autopilot Malfunction: Tesla's Mistake Recognizes Green, Not Red Traffic Lights

Recent incident highlights the importance of safe and secure AI in autonomous vehicles. This AI incident maps to the Govern function in HISP...

New York Police Department's AI Robot Dog Incident: A Case for Responsible AI Governance

The New York Police Department's AI robot dog incident highlights the need for safe and secure AI. This AI incident maps to the Govern funct...

Race Used as High-Impact Predictor in AI Systems at Major Universities: Raising Awareness for Safe and Secure AI

Recent findings highlight the use of race as a 'High Impact Predictor' in student success prediction models by major universities, showcasin...

The Emergence of 'Robo-Debt' in French Welfare Services: A Case Study for Responsible AI

Explore a concerning AI incident in France where welfare services are allegedly using automated systems to generate debt. This case highligh...

Discriminatory AI Allegation: Thousands of Families Accused Incorrectly of Fraud - Harm Prevention in Focus

This AI incident highlights the importance of trustworthy and responsible AI governance. The misuse of algorithms can lead to significant ha...

Struggles of Personal Voice Assistants with Black Voices Highlighted in New Study - Enhancing AI Trustworthiness

A recent study reveals challenges faced by personal voice assistants when interacting with black voices, underscoring the importance of resp...

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

This incident highlights the need for trustworthy AI, free from bias. The photo crop algorithm favored white faces and women, a clear violat...

Exploring California's Controversial AI-Driven Vaccine Allocation System: A Case Study in Responsible AI Governance

This AI incident maps to the 'Govern' function in HISPI Project Cerebellum Trusted AI Model (TAIM). The California 'Equity' algorithm, desig...

Autopilot Safety Debate: Tesla vs. Crash Victims

An examination of the ongoing debate surrounding Tesla's Autopilot system, addressing its claimed safety benefits versus the concerns raised...

Exploring User Data Protection Issues in a South Korean Chatbot Incident: A Call for Responsible AI

This AI incident involving a South Korean chatbot underscores the importance of data protection and privacy in AI systems. It highlights the...

AI Incident: Controversial Huawei Patent for Uighur Detection Sparks Concerns over Trustworthy AI

A recent patent disclosed by Huawei has raised concerns regarding the use of AI for mass surveillance, specifically in the detection of Uigh...

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.