Cited by 170Criminal Justice and Corrections AnalysisEthics and Social Impacts of AIArtificial Intelligence in Law

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

Berk, Richard·2017·Journal of Experimental Criminology

DOI 10.1007/s11292-017-9286-2

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Authors: Berk, R.
Affiliations: University of Pennsylvania (US)
Corresponding author: Berk, Richard
ORCID: Berk, Richard
Venue: Journal of Experimental Criminology
Publisher: Springer Science and Business Media LLC
Published: 2017-04-08
Volume: 13
Issue: 2
Pages: 193-216
ISSN: 1572-8315 (ISSN-L)
1573-3750
DOI: 10.1007/s11292-017-9286-2
OpenAlex: W2604660495
Cited by: 169
References: 52
Citations by year: 2026: 8 · 2025: 16 · 2024: 20 · 2023: 62 · 2022: 17 · 2021: 17 · 2020: 14 · 2019: 9 · 2018: 4 · 2017: 2
FWCI: 20.30
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (unspecified)
Locations: Journal of Experimental Criminology (publishedVersion)
Topics: Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Social Sciences › Law › Artificial Intelligence in Law
Keywords: parole decisions, recidivism, risk assessment, randomized experiments

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

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