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

Tricky YouTube Videos: A Harmful AI Incident Impacting Children's Safety

This disturbing incident involves manipulative YouTube videos targeting children, showcasing the importance of safe and secure AI for online...

Revising AI Practices: Changes in a Contentious Software Company

A series of negative media coverage has prompted a controversial software firm to reconsider its AI practices, aligning with responsible AI...

Examining the COMPAS Recidivism Algorithm: A Case Study in Responsible AI

This AI incident analysis sheds light on the COMPAS recidivism algorithm, emphasizing its impact on justice and highlighting the importance...

Debiasing Word Embeddings: Promoting Responsible AI through Gender Fairness

Explore the impact of biased word embeddings on AI systems and learn how to debias them for gender fairness. This AI incident maps to the Go...

Study Reveals Bias and Lack of Flexibility in AI Civility Detection: Addressing Harm Prevention through Responsible AI

A recent study highlights the potential for AI systems to exhibit bias and inflexibility in civility detection, underlining the need for rob...

Exploring Google's AI Misinterpretation of Homosexuality: A Case for Responsible AI Governance

This AI incident sheds light on the importance of safe and secure AI, highlighting a case where Google's AI demonstrated misguided opinions...

Amazon Alters Search Results for Trustworthy AI: Protecting Users from Potentially Harmful Content

The e-commerce giant Amazon has taken steps to modify its search rankings in relation to GLBT books, underscoring the importance of safe and...

Apology by Google for Racist Auto-Tag Incident in Photo App: A Reminder for Responsible AI Governance

Google recently apologized for a racially insensitive auto-tagging incident in its photo application. This AI incident highlights the need f...

Emotional Google Email Reply AI Incident: A Case Study in Responsible AI

Explore the incident where Google's email-replying AI consistently expressed affection, shedding light on the importance of trustworthy AI....

Unveiling the Unseen Gender Bias in Google Image Search: A Call for Trustworthy AI

Explore the hidden gender bias uncovered in Google Image Search, a stark reminder of the need for responsible AI governance. This AI inciden...

Investigation of Amazon Warehouse Bear Spray Accident: Highlighting the Importance of Safe and Secure AI

The Occupational Safety and Health Administration (OSHA) is currently investigating a bear spray accident at an Amazon warehouse that left a...

Exploring Potential Issues in Google's Ad-Targeting System: A Responsible AI Perspective

This analysis delves into a concern regarding Google's ad-targeting system, emphasizing the importance of trustworthy and safe AI. The incid...

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.