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

Examining Google's Image Search Algorithm Bias: A Case Study for Responsible AI

This incident involving racial bias in Google image search results highlights the need for trustworthy AI. The case, focusing on black teena...

Understanding and Mitigating Machine Bias: A Key Step Towards Trustworthy AI

Explore the challenges posed by machine bias in AI systems, and learn how we can develop safe and secure AI through the HISPI Project Cerebe...

Child Requests Music From Digital Assistant, Receives Inappropriate Content

This AI incident highlights the importance of responsible AI governance and safe guardrails. When a child asked a digital assistant for a so...

Amazon AI Misstep in Cell Phone Case Production: Unsuitable Design Issues

This AI incident involving Amazon's cell phone case production underscores the importance of trustworthy AI. It maps to the Govern function...

Examining the Impact of Robodebt on Human Services and AI Governance

In this article, we delve into the controversy surrounding Robodebt – a system that automated the debt recovery process for the Australian G...

Understanding the Role of Responsible AI in the Yandex Chatbot Incident - Contributing to Project Cerebellum

Explore the implications of the Yandex chatbot incident, a case study for trustworthy and safe AI. Learn how such incidents align with the G...

Google Translate Misidentifies Female Historians and Male Nurses for European Users: An AI Incident

This AI incident highlights the importance of responsible AI and safe and secure AI in language processing. Google Translate, a widely-used...

Apology Issued for Controversial Skin-Tone Altering Filter by FaceApp: An Examination of Responsible AI

FaceApp, a popular photo editing app, has faced backlash over its controversial 'racist' filter that lightens users' skin tone. This inciden...

Edit Wars on Wikipedia Highlight the Need for Responsible AI Governance

This AI incident demonstrates the importance of trustworthy and safe AI. As AI bots were used to enhance Wikipedia, unforeseen conflicts aro...

Lessons Learned from Kaggle's Fisheries Competition: Enhancing Trustworthy AI

Exploring the insights gained from Kaggle's fisheries competition, this article highlights the importance of responsible AI governance in re...

Improving AI's Capabilities in Writing Holiday Music: An Analysis of a Christmas Carol Incident

This AI incident offers an insightful look into the current limitations of AI in music composition, particularly in the creation of holiday...

Resolving Ski Photo Issues: A Case Study on Google Photos' AI Governance

Recent incident involving Google Photos highlights the importance of safe and secure AI governance. The photo-editing AI miscorrected a ski...

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.