Racial Bias in AI Search Results: An Unacceptable Incident of Untrustworthy AI
This incident underscores the importance of addressing racial bias in AI search results, a critical component of ensuring trustworthy and re...
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This incident underscores the importance of addressing racial bias in AI search results, a critical component of ensuring trustworthy and re...
Read moreThis analysis sheds light on a concerning allegation of gender bias in LinkedIn's search engine, emphasizing the need for trustworthy and re...
Read moreExplore the intersection of AI and labor markets through a case study on the National Residency Matching Program, a pioneering example of AI...
Read moreThis AI incident highlights the persistent issue of racial bias in AI systems, a crucial concern for trustworthy AI governance. Addressing a...
Read moreThis AI incident provides a vivid example of the importance of robust governance in AI systems, underscoring the need for trustworthy and sa...
Read moreExplore this incident involving algorithmic defamation, its impact on trustworthy AI, and how it maps to the Govern function in HISPI Projec...
Read moreRecent events have led to Google's decision to halt sales of its Nest Smart Smoke Alarm. This AI incident underlines the critical role trust...
Read moreExplore the incident where an AI was biased towards lighter skin tones in a beauty contest, shedding light on the importance of safe and sec...
Read moreIncident involving a crime-fighting robot rolling over a child highlights the importance of trustworthy AI governance. This AI incident maps...
Read moreExplore the significance of The DAO (organization) in promoting responsible AI, highlighting its impact on AI governance and trustworthiness...
Read moreThis incident demonstrates the potential risks of unregulated AI deployment. In this case, a robot hired to assist customers caused fear ins...
Read moreAn incident involving an AI-powered passport checker has raised concerns about the reliability and fairness of these systems. In this instan...
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.