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 Failure Files™

Israel police mistakenly arrest Palestinian man for writing ‘good morning’ on Facebook

A Palestinian man was arrested by Israeli police based on a Facebook post containing the phrase 'good morning'. The incident highlights the...

Israel Arrests Palestinian Because Facebook Translated 'Good Morning' to 'Attack Them'

An incident in Israel demonstrates the potential harm that can arise from inaccurate AI translation services, as a Palestinian was arrested...

Facebook apologizes after wrong translation sees Palestinian man arrested

A Facebook translation error led to the arrest of a Palestinian man in Jerusalem, underscoring the need for responsible AI and trustworthy A...

Is Pokemon Go racist?

Recent allegations have surfaced concerning potential racial bias within the popular augmented reality game, Pokemon Go. This article explor...

Is Pokémon Go Racist? Users Complain Of Lack Of Poké Stops In Black Areas

Recent complaints from users suggest a potential racial bias in the distribution of PokéStops within the augmented reality game, Pokémon Go....

Pokemon Go: The Good, The Bad, And The Ugly

In this article, we delve into a fascinating case study of Pokemon Go, exploring the intersection of AI, user experience, and responsible AI...

Pokemon Go accused of racism after more Poke Stops in white neighborhoods

The popular AR game, Pokemon Go, has been accused of racial bias following user complaints that more Poke Stops are located in predominantly...

How Nintendo changed this racist Pokémon's design for the better

Exploring Nintendo's decision to change the design of a controversial Pokémon, demonstrating their commitment to Safe and Secure AI. Learn a...

Power of Numbers: Pokemon Go!

Explore the effects of popular augmented reality game Pokémon GO on society, revealing insights into responsible AI governance and harm prev...

Analyzing Released NYC Value-Added Data Part 2

Exploring the implications, potential biases, and responsible data practices in the use of NYC value-added data for education policy and ass...

Master teacher suing New York state over ‘ineffective’ rating is going to court

A master teacher is taking legal action against the state of New York, claiming that their 'ineffective' rating is unjust. This incident rai...

New data show more than half of NYC teachers judged, in part, by test scores they don’t directly affect

Recent data reveals that over half of New York City teachers are evaluated, in part, by test scores they don't directly influence. This rais...

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.