Robotic Surgery Incidents Highlight Need for Safe AI Guardrails - 144 Deaths Since 2000
This robotic surgery incident study underscores the importance of trustworthy AI and robust safety measures in healthcare. With 144 reported...
Read moreValues Statement: We believe AI should cause no harm, but enhance the quality of human life, by proactively adopting our AI Governance framework.
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AI Incidents
Data source & citationGoogle's Autocomplete Function Modification Ordered in Japan - An Examination of AI Governance
In this article, we delve into the recent ruling requiring Google to modify its autocomplete function in Japan, highlighting the importance...
Read moreFaulty Feature Causes Temporary Halt in Sales of Google's Nest Smart Smoke Alarm - A Case for Safe and Secure AI
This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Understanding and addressing such issues i...
Read moreExamining LinkedIn's Denial of Alleged Gender Bias in AI Recommendations - A Look at Responsible AI Governance
This incident sheds light on the need for robust governance in AI systems, as it illustrates potential gender bias in LinkedIn's recommendat...
Read moreAI Bias Incident: New Zealand Passport Robot Discriminates against Applicants of Asian Descent
This AI incident highlights the need for trustworthy, safe, and secure AI governance. The robot incorrectly instructed an applicant of Asian...
Read morePotential Consequences of AI System Malfunctions: A Cautionary Tale for Businesses
Explore the repercussions of faulty AI systems in this insightful article, emphasizing the importance of responsible and trustworthy AI. Thi...
Read moreUnderstanding the Ethereum Crisis: The DAO, Hack, Soft Fork, and Hard Fork — Mapping to Govern Function in Project Cerebellum Trusted AI Model
Dive into a historic Ethereum crisis: The DAO hack, soft fork, and hard fork. Learn how these events demonstrated the importance of governan...
Read moreExploring the Incident with Tay (AI Bot): A Case Study on Responsible AI
Dive into the case of Tay, a conversational bot developed by Microsoft that generated controversial responses due to inappropriate content....
Read moreToddler Injured by Security Robot: A Case Study on AI Incident Safety
An unfortunate incident involving a toddler and a security robot in Silicon Valley highlights the importance of safe and secure AI systems....
Read moreTesla Autopilot Incident: Tragic Reminder of the Need for Responsible AI Governance
The unfortunate death of Joshua Brown in a Tesla self-driving accident serves as a grim reminder of the need for trustworthy, safe, and secu...
Read moreExamining Racial Bias in Google's Image Search Results: An Instance of Unfair AI Practices
This incident highlights the potential for racial bias in AI, an issue that underscores the importance of trustworthy and responsible AI gov...
Read moreUnderstanding and Mitigating Machine Bias: Key to Safe AI
Exploring the impact of machine bias in AI, its potential consequences on fairness and trustworthiness, and how you can help prevent harm th...
Read moreData 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.