Exploring Incident 139: A Deep Dive into Safe and Secure AI
Delve into the details of Incident #139, a critical examination that underscores the importance of trustworthy AI. This incident maps to the...
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 & citationExamining Incident #138: A Case Study of AI Governance
Dive into the details of incident #138, a pivotal example highlighting the importance of responsible AI governance. This AI incident maps to...
Read moreAnalyzing Incident #137: A Case Study of Safe and Secure AI Governance
Explore the findings of Incident #137, an instance highlighting the importance of robust governance in AI systems. This AI incident maps to...
Read moreExploring Incident 136: A Case Study in AI Governance
Dive into the details of Incident #136, an illuminating example of why safe and secure AI is crucial. This AI incident maps to the Govern fu...
Read moreExamining Incident #107: Unintended Consequences of AI Model
This AI incident sheds light on the unforeseen outcomes that can arise from AI models, underscoring the importance of trustworthy and safe A...
Read moreStruggles of Personal Voice Assistants with Black Voices Highlighted in New Study: The Need for Responsible AI Governance
A recent study reveals a significant problem: personal voice assistants struggle to understand black voices. This underscores the importance...
Read moreAI Incident 103: Examining a Critical Failure in AI Governance
Dive into the analysis of Incident #103, which underscores the importance of robust AI governance for safe and secure AI operations. This AI...
Read moreAI Incident 104: Unintended Consequences in Sentiment Analysis
This AI incident involving sentiment analysis software demonstrates the importance of responsible AI governance. The system, intended to ana...
Read moreExploring Incident #105 in Project Cerebellum's AI Incident Database: A Case Study for Safe and Secure AI
Dive into this in-depth analysis of incident #105, highlighting its implications on trustworthy AI and AI governance. Learn how this inciden...
Read moreExploring Incident #106 in AI Governance: Harm Prevention and the HISPI Project Cerebellum Trusted AI Model
Dive into a comprehensive analysis of AI Incident #106, revealing insights on trustworthy AI and its impact on harm prevention. Discover how...
Read moreAI Incident #110: Unintended Autocomplete Predictions Lead to Bias
Explore the impact of unintended autocomplete predictions causing bias in AI systems. This incident maps to the Govern function in HISPI Pro...
Read moreExploring Incident #112: An Examination of Responsible AI in Action
Dive into the analysis of Incident #112, a revealing look at how AI governance plays out in real-world scenarios. This incident underscores...
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.