Descripción: Police departments across the U.S. have used facial recognition software to identify suspects in criminal investigations, leading to multiple false arrests and wrongful detentions. The software's unreliability, especially in identifying people of color, has resulted in misidentifications that were not disclosed to defendants. In some cases, individuals were unaware that facial recognition played a role in their arrest, violating their legal rights and leading to unjust detentions.
Editor Notes: This collective incident ID, based on a Washington Post investigation, details many harm events, the overarching theme of which is widespread facial recognition technology assisting in arrests made by police departments across the United States combined with a lack of transparency about the technology's use in making the arrests. Some of the documented incidents in the Washington Post's investigation are as follows: (1) 2019: Facial recognition technology used to misidentify Francisco Arteaga in New Jersey, which led to his wrongful detention for four years (see Incident 816). (2) 2020-2024: Miami Police Department conducts 2,500 facial recognition searches, leading to at least 186 arrests and 50 convictions. Less than 7% of defendants were informed of the technology's use. (3) 2022: Quran Reid is wrongfully arrested in Louisiana due to a facial recognition match, despite never visiting the state (see Incident 515). (4) June 2023: New Jersey appeals court rules that a defendant has the right to information regarding the use of facial recognition technology in their case. (5) July 2023: Miami Police Department acknowledges that they may not have informed prosecutors about the use of facial recognition in many cases. (6) October 6, 2024: The Washington Post publishes its investigation on these incidents and practices.
Entidades
Ver todas las entidadesAlleged: Clearview AI developed an AI system deployed by Police departments , Evansville PD , Pflugerville PD , Jefferson Parish Sheriff’s Office , Miami PD , West New York PD , NYPD , Coral Springs PD y Arvada PD, which harmed Quran Reid , Francisco Arteaga y Defendants wrongfully accused by facial recognition.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.4. Lack of transparency or interpretability
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.
- 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
Informes del Incidente
Cronología de Informes
Cientos de estadounidenses han sido arrestados después de que se los relacionara con un crimen mediante un software de reconocimiento facial, según ha descubierto una investigación del Washington Post, pero muchos nunca lo saben porque la p…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.