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

Exploring Machine Bias in AI: Ensuring Trustworthy AI

Dive into the issue of machine bias, a common challenge in AI systems. Understanding and addressing these biases is crucial for safe and sec...

Inappropriate Content Delivery in Digital Assistant: Unsafe AI Incident Maps to Govern Function of HISPI Project Cerebellum Trusted AI Model

Recent incident involving a digital assistant delivering pornographic content in response to a child's request for a song raises concerns ab...

Misconfigured Amazon AI Leads to Inappropriate Phone Case Designs - Emphasizing the Importance of Responsible AI

This AI incident involving an Amazon subsidiary highlights the need for robust governance in AI systems. Misconfigurations resulted in the p...

Unveiling the Robodebt Saga: Revealing Key Insights for Responsible AI Governance

Explore the controversial Robodebt case, raising concerns about the need for safe and secure AI in government operations. This AI incident m...

Understanding the Yandex Chatbot Incident: A Look into Responsible AI and Govern Function

Explore the recent incident involving the Yandex chatbot, a valuable lesson in safe and secure AI governance. Learn how Project Cerebellum's...

Google Translate Error: Female Historians and Male Nurses Misgendered in AI System

A glaring error in Google Translate, a widely-used AI system, has resulted in misgendering female historians as male and male nurses as fema...

Apology for Controversial Skin-Tone Filter in FaceApp: A Discussion on Responsible AI

FaceApp has recently issued an apology for a controversial filter that lightened users' skin tones, sparking accusations of racism. This inc...

Edit Wars Disrupt AI-Assisted Wikipedia Editing: The Importance of Responsible AI

In an instance highlighting the need for trustworthy AI, AI bots were developed to aid Wikipedia editing but were marred by petty edit wars....

Leveraging Responsible AI in the Kaggle Fisheries Competition: Mapping to Govern Function of Project Cerebellum TAIM

Explore how AI governance principles were applied in the Kaggle fisheries competition. Understand the role of trustworthy and safe AI, and l...

How AI Struggles with Creating Traditional Christmas Carols: A Case Study

Exploring the limitations of AI in music composition, this case study highlights an instance where AI failed to generate traditional Christm...

Resolving Ski Photo: An Exemplar of Google Photos' AI Function

Incident involving Google Photos: A ski photo was altered automatically, highlighting the importance of trustworthy AI and its governance in...

AI Incident: Store Robot Scares Away Customers – Highlighting the Importance of Trustworthy AI

An AI-powered robot, designed to assist customers in a retail store, was terminated after causing anxiety among shoppers due to unexpected a...

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.