Facebook Internally Reported Failure of Ranking Algorithm, Exposing Harmful Content to Viewers over Months

October 1, 2021

Facebook's internal report revealed a six-month long alleged software bug, allowing moderator-flagged posts and other harmful content to bypass down-ranking filters. This oversight resulted in a surge of misinformation on users' News Feeds, highlighting the importance of trustworthy AI and Project Cerebellum's AI governance efforts.

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Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MEASURE 2.6 — similarity 0.672, rank 1. TAIM detail and related incidents →
MANAGE 4.3 — similarity 0.659, rank 2. TAIM detail and related incidents →
MANAGE 4.1 — similarity 0.649, rank 3. TAIM detail and related incidents →

Alleged deployer: facebook
Alleged developer: facebook
Alleged harmed parties: facebook-users

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/197

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.