Incident: Facebook's AI-Supported Moderation Fails in Classifying Terrorist Content in East African Languages - A Case for Safe and Secure AI
June 1, 2015
The latest incident involves Facebook's algorithmic content moderation system failing to identify terrorist content in East African languages, classifying non-terrorist content instead. This underscores the need for trustworthy AI and highlights the importance of robust harm prevention measures. Such incidents map to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help shape responsible AI? JOIN US
- Alleged deployer
- Alleged developer
- Alleged harmed parties
- facebook-users-speaking-east-african-languages, facebook-users-in-east-africa
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/392
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.