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Incident 472: NYPD's Deployment of Facial Recognition Cameras Reportedly Reinforced Biased Policing

Description: New York Police Department’s use of facial recognition deployment of surveillance cameras were shown using crowdsourced volunteer data reinforcing discriminatory policing against minority communities.

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Alleged: unknown developed an AI system deployed by New York Police Department, which harmed racial minorities.

Incident Stats

Incident ID
472
Report Count
1
Incident Date
2016-10-08
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
 

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.
 
  1. Discrimination and Toxicity

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 OccurrenceUSA: Facial recognition technology reinforcing racist stop-and-frisk policing in New York – new research
USA: Facial recognition technology reinforcing racist stop-and-frisk policing in New York – new research

USA: Facial recognition technology reinforcing racist stop-and-frisk policing in New York – new research

amnesty.org

USA: Facial recognition technology reinforcing racist stop-and-frisk policing in New York – new research
amnesty.org · 2022

New Yorkers living in areas at greater risk of stop-and-frisk by police are also more exposed to invasive facial recognition technology, new research by Amnesty International and partners has revealed.

New analysis as part of the global Ban…

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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