Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse

Incident 439: Detroit Police Wrongfully Arrested Black Man Due To Faulty Facial Recognition

Description: A Black man was wrongfully detained by the Detroit Police Department as a result of a false facial recognition (FRT) result.

Tools

New ReportNew ReportNew ResponseNew ResponseDiscoverDiscoverView HistoryView History

Entities

View all entities
Alleged: DataWorks Plus developed an AI system deployed by Detroit Police Department, which harmed Michael Oliver and Black people in Detroit.

Incident Stats

Incident ID
439
Report Count
3
Incident Date
2019-07-31
Editors
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
 

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 OccurrenceControversial Detroit facial recognition got him arrested for a crime he didn’t commitFaulty Facial Recognition Led to His Arrest—Now He’s SuingWrongful arrest exposes racial bias in facial recognition technology
Controversial Detroit facial recognition got him arrested for a crime he didn’t commit

Controversial Detroit facial recognition got him arrested for a crime he didn’t commit

freep.com

Faulty Facial Recognition Led to His Arrest—Now He’s Suing

Faulty Facial Recognition Led to His Arrest—Now He’s Suing

vice.com

Wrongful arrest exposes racial bias in facial recognition technology

Wrongful arrest exposes racial bias in facial recognition technology

cbsnews.com

Controversial Detroit facial recognition got him arrested for a crime he didn’t commit
freep.com · 2020

The high-profile case of a Black man wrongly arrested earlier this year wasn’t the first misidentification linked to controversial facial recognition technology used by Detroit Police, the Free Press has learned. 

Last year, a 25-year-old D…

Faulty Facial Recognition Led to His Arrest—Now He’s Suing
vice.com · 2020

Detroit police wrongfully arrested another Black man based on flawed facial recognition technology that often yields errors in identifying people of color, according to a new lawsuit obtained by Motherboard.

Michael Oliver, 26, was arrested…

Wrongful arrest exposes racial bias in facial recognition technology
cbsnews.com · 2020

In July of 2019, Michael Oliver, 26, was on his way to work in Ferndale, Michigan, when a cop car pulled him over. The officer informed him that there was a felony warrant out for his arrest. 

"I thought he was joking because he was laughin…

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.
Previous IncidentNext Incident

Research

  • Defining an “AI Incident”
  • Defining an “AI Incident Response”
  • Database Roadmap
  • Related Work
  • Download Complete Database

Project and Community

  • About
  • Contact and Follow
  • Apps and Summaries
  • Editor’s Guide

Incidents

  • All Incidents in List Form
  • Flagged Incidents
  • Submission Queue
  • Classifications View
  • Taxonomies

2023 - AI Incident Database

  • Terms of use
  • Privacy Policy
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • 30ebe76