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Incident 388: Facial Recognition Pilot in Bahia Reportedly Targeted Black and Poor People

Description: Facial recognition deployed in a pilot project by the local government of Bahia despite having minimal hit rate reportedly targeted Black and poor people disproportionately.

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Alleged: Huawei developed an AI system deployed by the government in Bahia and Bahia's Secretary of Public Security, which harmed Black people in Brazil and Black people in Bahia.

Incident Stats

Incident ID
388
Report Count
1
Incident Date
2018-12-01
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
 

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 OccurrenceBahia is becoming a facial recognition laboratory
Bahia is becoming a facial recognition laboratory

Bahia is becoming a facial recognition laboratory

theintercept.com

Bahia is becoming a facial recognition laboratory
theintercept.com · 2021
AI Translated

It was late afternoon. After leaving work, administrative assistant Davi was waiting for the last ride of the day with a friend at a bus stop on Avenida Paralela, in Salvador, when he was approached by a military police garrison. “I handed …

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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