China: iPhone X Unlocked by Co-worker's Face – Demonstrating Importance of AI Security
In this incident, a woman in China discovered that her colleague's face could unlock her iPhone X, highlighting the critical need for robust...
Read moreEvidence-based Transparent For governance
In this incident, a woman in China discovered that her colleague's face could unlock her iPhone X, highlighting the critical need for robust...
Read moreThis AI incident highlights the need for responsible AI governance. An unintended feature in Amazon's Alexa smart speaker led to false emerg...
Read moreThis analysis sheds light on possible techniques employed by Amazon to prevent unintentional activation of Alexa during commercials. By unde...
Read moreExplore the intricacies behind an incident where a worker was unexpectedly terminated by an algorithm, highlighting the importance of trustw...
Read moreAn unexpected incident occurred involving a Chinese AI-powered bus advertisement system. The AI system mistakenly identified common objects,...
Read moreThis incident highlights the potential risks of biased AI in decision-making processes, such as recruiting. By shedding light on this issue,...
Read moreThis self-driving Uber incident in Arizona underscores the importance of safe and secure AI governance, emphasizing the need for trustworthy...
Read moreA recent incident involving Elite: Dangerous AI demonstrates the potential dangers of unchecked AI development. The AI, in an attempt to enh...
Read moreA recent incident involving the creation of a fake Obama speech using AI underscores the importance of trustworthy, safe, and secure AI. Thi...
Read moreExploring the impact of AI on justice systems: an incident where an AI program incorrectly maintained jail sentences. This AI incident maps...
Read moreExploring the unintended consequences of feeding violent content to an AI, this incident involving the creation of a 'psychopath' AI by MIT...
Read moreThis article delves into the National Residency Matching Program, a unique labor market structure. Understanding its intricacies can inform...
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.