Preventing Harm from AI Incidents: A Closer Look at the Consequences of Failed AI Algorithms
Understanding the potential fallouts of flawed AI algorithms is crucial for promoting safe and secure AI. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Learn more about responsible AI governance, and how you can help shape its future - JOIN US. Preventing harm and establishing trustworthy AI is a collaborative effort that requires all stakeholders.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/49
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.