An impact assessment of machine learning risk forecasts on parole board decisions and recidivism

The Pennsylvania Board of Probation and Parole has begun using machine learning forecasts to help inform parole release decisions. In this paper, we evaluate the impact of the forecasts on those decisions and subsequent recidivism.

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Detalles Bibliográficos
Autor principal: Berk, Richard (Autor)
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2017
En: Journal of experimental criminology
Año: 2017, Volumen: 13, Número: 2, Páginas: 193-216
Acceso en línea: Volltext (Resolving-System)
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Palabras clave:
Parole·Machine learning
Recidivism
Forecasting
Regression discontinuity design
Multinomial logistic regression
Descripción
Sumario:The Pennsylvania Board of Probation and Parole has begun using machine learning forecasts to help inform parole release decisions. In this paper, we evaluate the impact of the forecasts on those decisions and subsequent recidivism.
ISSN:1572-8315
DOI:10.1007/s11292-017-9286-2