False Claims About COVID-19 and Voting Slip Through Facebook's Fact-Checking: Understanding the Govern Function in Project Cerebellum's Trusted AI Model
This case study highlights how false information regarding COVID-19 and voting can bypass Facebook's fact-checks. It underscores the importance of robust AI governance and guardrails for safe and secure AI, as exemplified in the Govern function within the HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help shape responsible AI? JOIN US
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/84
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.