Alleged Gender Discrimination in Facebook Job Ads Algorithm

June 12, 2023

Facebook's job ad delivery algorithm allegedly displayed job advertisements disproportionately to one gender, potentially reinforcing societal biases and limiting opportunities for certain groups. This incident underscores the importance of governance and responsible AI practices in preventing harm. For those interested in shaping the future of trustworthy AI, JOIN US. This case study maps to the HISPI Project Cerebellum TAIM's Govern function, emphasizing the need for strong guardrails for AI.

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Matched TAIM controls

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

GOVERN 3.1 — similarity 0.663, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.651, rank 2. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.638, rank 3. TAIM detail and related incidents →

Alleged deployer: meta
Alleged developer: meta
Alleged harmed parties: women, underrepresented-genders, general-public, advertisers

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/580

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.