Addressing AI Incident #29: A Case Study in Responsible Harm Prevention
Exploring the lessons learned from incident #29, we delve into the challenges posed by unforeseen consequences in AI systems. This case study underscores the importance of robust safeguards for AI governance and the need for trustworthy models. By leveraging our AI incident database and HISPI Project Cerebellum TAIM (Trusted AI Model), we aim to provide guardrails that ensure safe and secure AI development, promoting responsible harm prevention. Through JOIN US, contributors can join us in shaping the future of AI.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/29
Data 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.