Incidente 274: translated-es-Virginia Courts’ Algorithmic Recidivism Risk Assessment Failed to Lower Incarceration Rates
Descripción: translated-es-Virginia courts’ use of algorithmic predictions of future offending risks were found by researchers failing to reduce incarceration rates, showed racial and age disparities in risk scores and its application, and neither exacerbated or ameliorated historical racial differences in sentencing.
Entidades
Ver todas las entidadesAlleged: Virginia Department of Criminal Justice Services developed an AI system deployed by Virginia courts, which harmed Virginia convicted felons , Virginia Black offenders y Virginia young offenders.
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.
- Discrimination and Toxicity
Entity
Which, if any, entity is presented as the main cause of the risk
Other
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
Informes del Incidente
Cronología de Informes
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Tendemos a suponer que el futuro a corto plazo de la automatización se basará en asociaciones hombre-máquina. Nuestros compinches robóticos compensarán las blandas ineficiencias del cerebro humano, mientras que el juicio humano lijará sus f…
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Evaluamos los impactos de la adopción de evaluaciones de riesgo algorítmicas como una ayuda para la discreción judicial en la sentencia por delitos graves. Encontramos que las decisiones de los jueces están influenciadas por el puntaje de r…
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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