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Incident 518: New York Detective Misused Woody Harrelson's Face to Perform Face Recognition Search

Description: When the facial recognition search for a CVS theft suspect's face returned no useful matches due to the surveillance footage being obscured and highly pixelated, a New York City police detective continued the face search using Woody Harrelson's face allegedly due to his resemblance to the suspect's face, eventually leading to the arrest of an unknown victim.

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Alleged: developed an AI system deployed by New York Police Department and Facial Identification Section, which harmed unknown.

Incident Stats

Incident ID
518
Report Count
1
Incident Date
2017-04-28
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
 

7.3. Lack of capability or robustness

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. AI system safety, failures, and limitations

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 OccurrenceGarbage In, Garbage Out: Face Recognition on Flawed Data
Garbage In, Garbage Out: Face Recognition on Flawed Data

Garbage In, Garbage Out: Face Recognition on Flawed Data

flawedfacedata.com

Garbage In, Garbage Out: Face Recognition on Flawed Data
flawedfacedata.com · 2019

Introduction

On April 28, 2017, a suspect was caught on camera reportedly stealing beer from a CVS in New York City. The store surveillance camera that recorded the incident captured the suspect’s face, but it was partially obscured and hig…

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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