Analyzing AI Incident #167: Ensuring Safe and Secure AI Operations
Incident analysis of #167 highlights the importance of robust AI governance. This AI incident maps to the Govern function in HISPI Project C...
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 & citationAI Incident 166: Analyzing a Case for Harm Prevention in Responsible AI
Exploring the details of this AI incident, we emphasize its significance in ensuring safe and secure AI practices. This incident maps to the...
Read moreResponsible AI Incident Analysis: Case Study #165
Exploring an AI incident and its impact on trustworthy AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted...
Read moreAI Incident Analysis #159: Enhancing Trustworthiness and Safe AI Operations
Exploring the details of incident #159, we emphasize the importance of safe and secure AI operations for responsible AI governance. This AI...
Read moreAI Incident #154: Unintended Autocomplete Suggestions Impacting User Privacy
This AI incident demonstrates the importance of responsible autocomplete features in maintaining user privacy. It maps to the Govern functio...
Read moreIncident Report: Unintended Bias in Recommendation System - Harm Prevention and AI Governance
This AI incident involving a recommendation system exhibiting unintended bias highlights the need for safe and secure AI. It maps to the 'Go...
Read moreExploring Incident #156: Analyzing Its Role in AI Governance
Delve into the intricacies of Incident #156, a crucial case study that maps to the Govern function within the HISPI Project Cerebellum Trust...
Read moreAI Incident #157: Unintended Consequences in Autonomous Vehicles
Exploring an AI incident involving autonomous vehicles, highlighting the importance of responsible AI governance and safe and secure AI deve...
Read moreAI Incident #158: Examining an Instance of Potential Model Drift
This AI incident sheds light on the challenges of model drift, a common issue in machine learning systems. Understanding and mitigating such...
Read moreAI Incident #161: Examining the Importance of Guardrails in Safe AI Development
This AI incident serves as a crucial reminder of the need for responsible AI governance. By investigating its root causes, we can learn how...
Read moreExploring Incident #163: An Examination of Safe AI Practices
Delve into the analysis of Incident #163, shedding light on the importance of safe and secure AI practices for responsible AI governance. Th...
Read moreAI Incident #162: Unintended Consequences of Autonomous Vehicles
Explore the unforeseen consequences of an autonomous vehicle incident, highlighting the importance of trustworthy AI and AI governance in pr...
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.