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

Thousands Accused of Fraud by Discriminatory AI Algorithm: A Case for Responsible AI Governance

Explore the consequences of a biased algorithm, learn how such incidents map to the Govern function in HISPI Project Cerebellum Trusted AI M...

Study Highlights Challenges in AI Voice Recognition for Black Voices: An Opportunity to Foster Trustworthy AI

A recent study reveals struggles in voice recognition for black voices by personal voice assistants. This underscores the importance of resp...

AI Incident Analysis #120: Examining Harm Prevention in Responsible AI

Dive into the details of AI Incident #120, shedding light on its implications for trustworthy AI and safe AI governance. Understanding these...

AI Incident 115: Understanding the Implications and Preventing Harm

Delve into AI Incident #115, its impact on trustworthy AI practices, and the role of Project Cerebellum's Govern function in maintaining saf...

AI Incident 116: Unintended Consequences of Autonomous Vehicle Decision-Making

Exploring a real-world AI incident involving an autonomous vehicle, this article highlights the importance of safe and secure AI in autonomo...

AI Incident 117: Unintended Consequences of Autonomous Vehicles - A Case Study on Responsible AI

This AI incident demonstrates the unintended consequences of autonomous vehicles, highlighting the importance of responsible AI and governan...

Exploring Incident #118 in the AI Landscape: Promoting Safe and Secure AI

Dive into Incident #118, a valuable learning opportunity for safe and secure AI development. This incident maps to the Govern function in HI...

Exploring Incident #119: A Deep Dive into Responsible AI

Delve into the details of Incident #119, a valuable learning opportunity that sheds light on the importance of trustworthy and safe AI. This...

Responsible AI Incident Analysis #122: Understanding the Impact on Safe and Secure AI

Incident analysis of #122 highlights a significant event in our AI governance landscape. This AI incident maps to the Govern function in HIS...

Incident Report: Unintended Bias in Predictive Modeling System

Explore the unintended bias incident in a predictive modeling AI system, highlighting its impact on fairness and accountability in AI. This...

Resolved AI Incident #123: A Case Study in Responsible AI Governance

This AI incident, incident #123, demonstrates the importance of robust governance mechanisms for responsible AI development and deployment....

Unsafe Autonomous Vehicle Incident: Highlighting the Need for Responsible AI

Exploring a recent autonomous vehicle incident that underscores the importance of trustworthy, safe, and secure AI. This AI incident maps to...

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.