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Incident 408: Facebook Reportedly Outed Sex Workers through Friend Recommendations

Description: Facebook's "People You May Know" feature reportedly outed sex workers by recommending clients to their personal accounts or family members to their business accounts with no option to opt out.

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Alleged: Facebook developed and deployed an AI system, which harmed sex workers using Facebook.

Incident Stats

Incident ID
408
Report Count
1
Incident Date
2017-04-15
Editors
Khoa Lam
Applied Taxonomies
MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

2.1. Compromise of privacy by obtaining, leaking or correctly inferring sensitive information

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.
 
  1. Privacy & Security

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

Incident OccurrenceHow Facebook Outs Sex Workers
How Facebook Outs Sex Workers

How Facebook Outs Sex Workers

gizmodo.com

How Facebook Outs Sex Workers
gizmodo.com · 2017

Leila has two identities, but Facebook is only supposed to know about one of them.

Leila is a sex worker. She goes to great lengths to keep separate identities for ordinary life and for sex work, to avoid stigma, arrest, professional blowba…

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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