Exploring Incident 29: Harm Prevention in AI Governance
Delve into the details of Incident #29, a valuable lesson in safe and secure AI practices. This incident maps to the Govern function in HISP...
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 & citationThe 2010 Flash Crash: An Illustration of the Need for Responsible AI Governance
On May 6, 2010, a rapid sequence of events triggered the largest one-day stock market drop in history - the infamous 'Flash Crash'. This AI...
Read moreSoviet Nuclear False Alarm Incident: A Cautionary Tale on AI Governance
This historic incident underscores the importance of responsible AI and safe and secure systems. The false alarm, triggered by an AI system,...
Read moreFace ID Breach Claim: Highlighting the Importance of Secure AI Systems
In the week following the iPhone X release, hackers claimed they managed to bypass Face ID, emphasizing the significance of secure and trust...
Read moreNear-Miss Incident Between Two Autonomous Vehicles: Highlighting the Need for Safe and Secure AI
This incident involving a driverless car near-miss with a Google car underscores the importance of responsible AI governance in road safety....
Read moreGermany: Worker Death Triggers Discussion on Responsible AI and Safe Automation - Incident Maps to the Govern Function in HISPI Project Cerebellum Trusted AI Model (TAIM)
A recent incident at a Volkswagen plant, where a robot caused a fatal accident, underscores the need for trustworthy AI and safe automation....
Read moreCrash Involving Self-Driving Bus Highlights Need for Robust AI Governance
A self-driving bus was involved in a crash less than two hours after its launch in Las Vegas, underscoring the importance of robust AI gover...
Read moreBias in Google's Sentiment Analysis API: A Cautionary Tale for Responsible AI
Google's sentiment analysis API has been found to mirror human biases, underscoring the need for trustworthy and safe AI. This incident maps...
Read moreGoogle Photos Misidentifies Gorillas: An Incident Highlighting the Need for Trustworthy AI
In this incident, Google Photos misclassified images of gorillas, demonstrating a lack of accuracy in AI systems. This underscores the impor...
Read moreCensorship of LGBTQ+ Content on Amazon's Platform: An Examination
Exploring the recent incident where gay books were censored on Amazon, this article underscores the need for safeguards in AI systems to pre...
Read moreEnhancing Trustworthy AI: Analyzing the Introduction of Smart Reply in Inbox by Gmail
Explore the implications of Google's Smart Reply feature in Inbox by Gmail on trustworthy AI, focusing on potential benefits and risks. This...
Read moreGoogle's Comment-Ranking System and Potential Alignment with Alt-Right: A Cautionary Tale on AI Governance
This incident involving Google's comment-ranking system sheds light on the need for robust AI governance, ensuring safe and secure AI. It hi...
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.