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Incident 315: Facial Recognition Service Abused to Target Russian Porn Actresses

Description: The facial recognition software FindFace allowing its users to match photos to people’s social media pages on Vkontakte was reportedly abused to de-anonymize and harass Russian women who appeared in pornography and alleged sex workers.

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Alleged: NtechLab developed and deployed an AI system, which harmed Russian pornographic actresses and Russian sex workers.

Incident Stats

Incident ID
315
Report Count
1
Incident Date
2016-04-09
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
 

4.3. Fraud, scams, and targeted manipulation

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. Malicious Actors & Misuse

Entity

Which, if any, entity is presented as the main cause of the risk
 

Human

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
 

Intentional

Incident Reports

Reports Timeline

Incident OccurrenceFacial Recognition Service Becomes a Weapon Against Russian Porn Actresses
Facial Recognition Service Becomes a Weapon Against Russian Porn Actresses

Facial Recognition Service Becomes a Weapon Against Russian Porn Actresses

advox.globalvoices.org

Facial Recognition Service Becomes a Weapon Against Russian Porn Actresses
advox.globalvoices.org · 2016

The developers behind “FindFace,” which uses facial recognition software to match random photographs to people’s social media pages on Vkontakte, say the service is designed to facilitate making new friends. Released in February this year, …

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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