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

Exploring Incident #153: Analyzing a Crucial Moment in Safe and Secure AI

Dive into the details of Incident #153, a vital learning opportunity showcasing responsible AI governance. This AI incident maps to the Gove...

Resolving Incident #152: Ensuring Safe and Secure AI Operations

Exploring the resolution of Incident #152, this analysis highlights the importance of trustworthy AI and robust AI governance. This AI incid...

AI Incident 151: Unintended Consequences in Predictive Modeling - Understanding Trustworthy AI

Explore the lessons learned from Incident #151, which demonstrates the importance of responsible AI and safe predictive modeling. This AI in...

Incident Report #150: Unintended Autonomous Vehicle Collision – A Case for Responsible AI Governance

Explore the details of Incident #150, an unfortunate collision involving an autonomous vehicle. This AI incident underscores the importance...

AI Incident 149: Understanding Its Role in Responsible AI Governance

This AI incident highlights the need for robust governance mechanisms in responsible AI, aligning with our efforts at Project Cerebellum. By...

Exploring Incident 148: A Deep Dive into AI Safety

This AI incident serves as an enlightening case study in the realm of AI governance, demonstrating the importance of safe and secure AI syst...

Exploring Incident #147 in AI Governance: Harm Prevention and the Trustworthy AI Model

Dive into Incident #147, a valuable learning opportunity on AI governance and harm prevention. This incident maps to the Govern function in...

Examining Incident #138: A Case Study of AI Governance

Dive into the details of incident #138, a pivotal example highlighting the importance of responsible AI governance. This AI incident maps to...

AI Incident #140: Analyzing a Potential Issue in AI System

This AI incident offers valuable insights into the challenges faced by AI systems, demonstrating the need for robust safeguards and governan...

Exploring Incident 139: A Deep Dive into Safe and Secure AI

Delve into the details of Incident #139, a critical examination that underscores the importance of trustworthy AI. This incident maps to the...

Incident Report: Unintended Consequences of Autonomous Vehicles – A Case Study

Explore the recent autonomous vehicle incident #141, shedding light on the potential risks and unintended consequences of AI in transportati...

Analyzing Incident #137: A Case Study of Safe and Secure AI Governance

Explore the findings of Incident #137, an instance highlighting the importance of robust governance in AI systems. 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.