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

Examining Misleading AI Claims in Medicine: Harm Prevention and Responsible AI

This AI incident highlights the importance of safe and secure AI, especially in critical areas such as medicine. It maps to the Govern funct...

AI in Healthcare: Unveiling Potential Bias in X-Ray Analysis - A Case for Responsible AI

An investigation uncovered racial bias in algorithms analyzing X-rays, raising concerns about AI fairness and safety. This AI incident maps...

California's New Legislation Targeting Amazon: A Step Towards Responsible AI Governance

California's recently passed warehouse worker bill represents a significant stride in AI governance, addressing concerns over working condit...

Three Robots Collision Sparks Warehouse Fire at Ocado: A Case for Safe and Secure AI

In this incident, three robots collided in an Ocado warehouse causing a fire. This AI incident maps to the Govern function in HISPI Project...

Microsoft's Controversial Move Towards AI Journalism: A Look at AI Governance

In a move that raises questions about the future of journalism, Microsoft has reportedly let go of human journalists to replace them with ro...

Ethical Guardrails for AI: Tech Companies Embrace Responsible AI Governance

Explore how tech companies are implementing ethical guardrails in their AI systems, contributing to the development of trustworthy AI. This...

Unwanted Cross-Association of Violent Content by Facebook's AI Moderator: A Case Study

This AI incident involving Facebook's video moderation system demonstrates the challenges in maintaining trustworthy AI. The system incorrec...

Ethnicity Detection Algorithm Incident: Alibaba Cloud Unit Faces Criticism

Alibaba's cloud unit is under scrutiny due to an ethnicity detection algorithm issue. The incident raises concerns about AI bias and the nee...

AI-Flagged California Bar Exam Applicants for Suspected Cheating Highlights Importance of Trustworthy AI

The recent California Bar Exam, in which AI identified a third of applicants suspected of cheating, underscores the crucial role of trustwor...

The Impact of TikTok Anorexia Content: A Case Study on AI Governance in Social Media

This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). The misuse of hashtags by pro-anorexia con...

Tragic Tesla Autopilot Incident: Passenger Watched Harry Potter While Driving, Highlighting the Need for Responsible AI

This Tesla incident underscores the importance of responsible AI governance. The driver's inattention while using autopilot tragically led t...

Ensuring Safe and Secure AI in Law Enforcement: A Closer Look

Explore this incident, which maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM), and how it contributes to shap...

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.