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Incident 288: New Jersey Police Wrongful Arrested Innocent Black Man via FRT

Description: Woodbridge Police Department falsely arrested an innocent Black man following a misidentification by their facial recognition software, who was jailed for more than a week and paid thousands of dollar for his defense.

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Alleged: unknown developed an AI system deployed by Woodbridge Police Department, which harmed Nijeer Parks.

Incident Stats

Incident ID
288
Report Count
4
Incident Date
2019-01-30
Editors
Khoa Lam
Applied Taxonomies
GMF, 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
 

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 Occurrence+3
He spent 10 days in jail after facial recognition software led to the arrest of the wrong man, lawsuit says
He spent 10 days in jail after facial recognition software led to the arrest of the wrong man, lawsuit says

He spent 10 days in jail after facial recognition software led to the arrest of the wrong man, lawsuit says

nj.com

Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match

Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match

nytimes.com

Black man in New Jersey misidentified by facial recognition tech and falsely jailed, lawsuit claims

Black man in New Jersey misidentified by facial recognition tech and falsely jailed, lawsuit claims

nbcnews.com

Government Users of Facial Recognition Software Sued by Plaintiff Alleging Wrongful Imprisonment Over Case of Mistaken Identity

Government Users of Facial Recognition Software Sued by Plaintiff Alleging Wrongful Imprisonment Over Case of Mistaken Identity

natlawreview.com

He spent 10 days in jail after facial recognition software led to the arrest of the wrong man, lawsuit says
nj.com · 2020

Editor’s note: This article has been updated to include a statement from the New Jersey Attorney General’s Office.

When Nijeer Parks walked out of a New Jersey prison in 2016, he returned to his family in Paterson and told them he was done …

Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match
nytimes.com · 2020

In February 2019, Nijeer Parks was accused of shoplifting candy and trying to hit a police officer with a car at a Hampton Inn in Woodbridge, N.J. The police had identified him using facial recognition software, even though he was 30 miles …

Black man in New Jersey misidentified by facial recognition tech and falsely jailed, lawsuit claims
nbcnews.com · 2020

A New Jersey man sued police and prosecutors, claiming he was wrongly arrested and jailed after facial recognition software mistakenly linked him to a hotel theft.

Nijeer Parks, 33, a Black man from Paterson, said his grandmother told him o…

Government Users of Facial Recognition Software Sued by Plaintiff Alleging Wrongful Imprisonment Over Case of Mistaken Identity
natlawreview.com · 2021

It has become commonplace for government agencies and law enforcement, particularly in large metropolitan areas, to use facial recognition software. These entities are a major client base of Clearview AI (“Clearview”), as we disclosed last …

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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