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

TAIM catalog Map Data source & citation

Investigations reveal lack of attention by Tesla driver before fatal accident

Recent findings suggest that the driver of a Tesla vehicle involved in a fatal crash was not watching a video at the time of the incident, a...

Exploring Responsible AI: The Tesla Autopilot Incident - Was the Driver Distracted?

In an incident that highlights the importance of AI governance, a Tesla vehicle using its Autopilot system was involved in a fatal crash. In...

Tragic Tesla Auto-Drive Incident: Passenger Allegedly Not Attentive

In a troubling incident, a Tesla vehicle on autopilot was involved in a fatal crash. Preliminary reports suggest that the passenger may not...

Algorithmic Bias: Examining Google's Display of Racially Skewed Results

An examination of a troubling incident where Google's search algorithm disproportionately displayed racist results for queries about black a...

Google's 'three black teenagers' search reveals biased societal norms

A recent experiment showcasing Google's autocomplete function highlighting racial stereotypes has sparked a conversation about AI and uncons...

Race Bias in AI: A Case Study of Google Search Trends

Explore the striking disparities between Google search trends for 'black teenagers' and 'white teenagers', shedding light on the need for re...

Bias in AI Image Search: Evil Mugshots versus Happy Stock Photos

A study highlights racial bias in Google Images' auto-complete search results, displaying mugshots for Black individuals and stock photos fo...

Bias in Search Results: The Impact of Race on Google's Algorithm

An interesting study by the University of Washington reveals racial bias in Google search results when queries involve Black individuals. Th...

Bias in Google Image Search: A Harmful Consequence of Unregulated AI

Recent studies have uncovered a shocking disparity in Google's image search results when querying 'Three Black Teenagers' versus 'Three Whit...

Exploring Bias in AI Image Search: A Closer Look at Google's Algorithm

Recent social media posts claim that searching 'Three Black Teenagers' on Google yields different results compared to 'Three White Teenagers...

Algorithmic Bias: Google Image Search Results Showcase Disparity

Recent studies have unveiled a striking disparity in Google's image search results when comparing the phrases 'Three Black Teenagers' and 'T...

Bias in AI-Powered Image Search: Google's Three Teenagers Incident

A recent study comparing image search results for 'three black teenagers' and 'three white teenagers' on Google revealed a striking disparit...

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.