Incident 416: Facebook's Job Ad Algorithm Allegedly Biased against Older and Female Workers

Description: Facebook's algorithm was alleged in a complaint by Real Women in Trucking to have selectively shown job advertisements disproportionately against older and female workers in favor of younger men for blue-collar positions.

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Alleged: Meta Platforms and Facebook developed and deployed an AI system, which harmed Real Women in Trucking and older female blue-collar workers.

Incident Stats

Incident ID
416
Report Count
3
Incident Date
2022-12-01
Editors
Khoa Lam
Applied Taxonomies
MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

1.1. Unfair discrimination and misrepresentation

Risk Domain

  1. Discrimination and Toxicity

Entity

AI

Timing

Post-deployment

Intent

Unintentional

Are Facebook job ads discriminatory? Company accused of bias against women, older workers
eu.usatoday.com · 2022

A female truckers association is accusing Meta Platforms of algorithmic bias, alleging its Facebook platform selectively shows job advertisements based on users' gender and age, with older workers far less likely to see ads and women far le…

Facebook Job Ads Illegally Discriminate, Female Truckers Say
bloomberg.com · 2022

Meta Platforms Inc. "routinely discriminates" in steering job ads to specific age and gender groups on its Facebook platform, a women's truckers organization alleged in a civil rights complaint.

"Facebook's algorithm regularly acts like rec…

Female truckers group alleges Facebook’s ad system is discriminatory
washingtonpost.com · 2022

An advocacy group representing female truck drivers filed a complaint Thursday with the Equal Employment Opportunity Commission alleging Facebook parent company Meta is steering ads for lucrative jobs away from women and older workers based…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
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