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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Bibliographische Detailangaben
1. VerfasserIn: Berk, Richard (VerfasserIn)
Medienart: Elektronisch Aufsatz
Sprache:Englisch
Veröffentlicht: 2017
In: Journal of experimental criminology
Jahr: 2017, Band: 13, Heft: 2, Seiten: 193-216
Online Zugang: Volltext (Resolving-System)
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Schlagwörter:
Forecasting
Multinomial logistic regression
Parole·Machine learning
Recidivism
Regression discontinuity design
Beschreibung
Zusammenfassung: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