Description: Facebook's ad delivery algorithm allegedly disproportionately showed job advertisements to one gender. Despite claims of non-discrimination, the algorithm's actions seem to perpetuate societal biases, which in turn could potentially limit opportunities for certain groups and hinder gender equity in the workplace.
Entities
View all entitiesAlleged: Meta developed and deployed an AI system, which harmed Women , Underrepresented genders , General public and Advertisers.
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
1.1. Unfair discrimination and misrepresentation
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Discrimination and Toxicity
Entity
Which, if any, entity is presented as the main cause of the risk
AI
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline
All the ads that we posted were shown - via one of Facebook’s mandatory ad campaign objectives – to users that Facebook thought were most likely to click on the website they linked to. And for all the ads, we specified only the following: t…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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