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

Five AI Incidents from 2017 Demonstrating the Need for Responsible AI Governance

Explore these five incidents that underscore the importance of safe and secure AI. This AI incident maps to the Govern function in HISPI Pro...

5 Notable AI Incidents from 2017 Highlighting the Need for Responsible AI Development

Exploring five significant AI incidents of 2017 that underscore the importance of safe, secure, and trustworthy AI. This AI incident maps to...

5 Significant AI Incidents from 2017 Demonstrating the Need for Responsible AI

Exploring five notable AI failures of 2017, this article highlights the importance of safe and secure AI. Understanding these incidents maps...

Examining Tesla's Challenges: The Importance of Safe and Secure AI Governance

Tesla's factory issues underscore the need for trustworthy AI governance. This AI incident maps to the 'Govern' function in HISPI Project Ce...

AI Incident 29: Unintended Consequences of Autonomous Vehicle Decision-Making

This AI incident involving an autonomous vehicle demonstrates the need for robust safety mechanisms in AI decision-making. It maps to the Go...

The 2010 Stock Market Flash Crash: An Example of AI Incident and the Need for Responsible Governance

This AI incident, the 2010 Stock Market Flash Crash, underscores the importance of responsible AI governance. Its consequences highlight the...

Unfair Bias in AI-Powered Online Advertising: A Case Study

Explore the consequences of discrimination in online ad delivery, a prime example of unintended biases in AI. Learn how this AI incident map...

Exploring AI Limits: The Latest Turing Test Reveals Shortcomings in Chatbot Intelligence

This AI incident, involving a challenging Turing test, exposes vulnerabilities in the logic and reasoning abilities of modern chatbots. It s...

Self-Driving Autopilot Incident in California: Highlighting the Importance of Responsible AI Governance

The tragic incident involving Tesla's Autopilot system underscores the need for trustworthy, safe, and secure AI. This AI incident maps to t...

Bel-Air Wildfire: AI Predictive Models Forecast Potential Spread, Highlighting Importance of Trustworthy AI

The Bel-Air wildfire serves as a stark reminder of the importance of trustworthy and reliable AI in predicting and managing disasters. This...

Examining Google Image Search's Gender Bias: A Responsible AI Issue

Uncovering a potential gender bias in Google Image Search raises awareness for the need of trustworthy AI and safe and secure AI practices....

Exploring the Implementation of Smart Reply in Inbox by Gmail: An Analysis of AI's Role in Email Automation

Dive into the latest development: Smart Reply in Inbox by Gmail. This AI feature showcases the growing integration of automation in our emai...

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.