Addressing Bias in AI: The Case of 'Racist in the Machine'
This article delves into an incident involving a biased algorithm that displayed racist outcomes. Highlighting the importance of responsible...
Read moreEvidence-based Transparent For governance
This article delves into an incident involving a biased algorithm that displayed racist outcomes. Highlighting the importance of responsible...
Read moreAn in-depth analysis of the Electric Elves incident, a poignant reminder of the intricate web of factors that can impact responsible AI depl...
Read moreThis study reviews 14 years of adverse events data from the Food and Drug Administration (FDA) related to robotic surgery. The findings high...
Read moreOver the past two decades, robotic surgery has become increasingly popular for a variety of procedures. However, recent reports have linked...
Read moreA recent study sheds light on the issues encountered during robotic surgery, emphasizing the importance of trustworthy AI governance and har...
Read moreExploring the safety of robotic surgeries involves scrutinizing the underlying AI models, their governance, and their impact on patient outc...
Read moreIn an alarming development, a study has unveiled 144 deaths potentially connected to robotic surgery procedures carried out in the United St...
Read moreIn an alarming incident, it has been reported that robot-assisted surgeries resulted in the deaths of 144 patients and injuries to 1,391 oth...
Read moreAn analysis of over a decade's worth of data reveals 144 fatal incidents associated with robotic surgery. This underscores the need for resp...
Read moreA recent study reveals a concerning correlation between robotic surgery and mortality rates in the United States. From 2000 to 2013, approxi...
Read moreExploring the impact of unsuccessful robotic surgeries on 144 patients and the urgent need for safe, secure, and trustworthy AI governance i...
Read moreRobotic surgery, a promising advancement in the medical field, faces recurring challenges that affect its efficacy. Incidents of malfunction...
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.