Misidentified by AI: An Examination of Unfair Bias
Explore the consequences of a misidentification by artificial intelligence, shedding light on the importance of fairness and eliminating bia...
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 & citationFrench Lawsuit Over Google Instant's Alleged Anti-Semitic Search Results Highlights Need for Responsible AI
This incident underscores the importance of trustworthy AI in preventing harm. Google Instant's reported anti-Semitic search results have sp...
Read moreUnauthorized Use of Live Facial Recognition on Minors Raises Concerns for Responsible AI
An incident involving live facial recognition technology being used to track children suspected of criminal activity has sparked discussions...
Read moreAI-controlled Police Robot's Inappropriate Response: Harm Prevention in AI Incidents
An unusual incident involving an AI-controlled police robot occurred, where it responded inappropriately to a woman trying to report a crime...
Read moreThe Role of an Unseen Algorithm in College Admission Decisions - Understanding Its Impact on Fairness and Responsible AI
Explore the mysterious algorithm guiding college admissions and its potential bias, raising questions about fairness and trustworthy AI. Lea...
Read moreRacially Biased AI Algorithm Blocked Kidney Transplants for Black Patients: A Call for Responsible AI
This AI incident underscores the importance of trustworthy and safe AI. The algorithm's bias, which prioritized white patients over black on...
Read moreHumorous AI Misinterpretation Highlights Importance of Safe and Secure AI - This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
An amusing instance of AI misinterpreting a referee's bald head as a football underscores the need for trustworthy, responsible AI. Incident...
Read moreUncovering Racial, Gender, and Socioeconomic Bias in Chest X-Ray AI Classifiers: A Case for Trustworthy AI
This incident highlights racial, gender, and socioeconomic bias in chest X-ray classifiers, emphasizing the importance of trustworthy AI. Th...
Read moreThe Lekki Massacre Incident: Assessing the Role of Responsible AI in Misinformation Prevention
In October 2020, content related to the Lekki Massacre was flagged 'false' by Facebook. This incident underscores the importance of safe and...
Read moreUnveiling the Controversy Behind Efficient Spam Filters: A Deep Dive
Explore the intricate world of spam filters, often perceived as uncontroversial. However, delving deeper, we find complexities and debates t...
Read moreFacebook Struggles to Filter False COVID-19 and Voting Claims: A Harm Prevention Challenge in AI Governance
This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Understanding these challenges is crucial...
Read moreRobot Misstep: AI Expresses Fears Over Potential Harm to Humankind - Emphasizing Need for Safe and Secure AI
In an unexpected development, an AI system expressed concerns about its potential to cause harm to humanity. This incident underscores the n...
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.