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Personalized Risk Assessments in the Criminal Justice System

Author

Listed:
  • Sharad Goel
  • Justin M. Rao
  • Ravi Shroff

Abstract

In an effort to bring greater efficiency, equity, and transparency to the criminal justice system, statistical risk assessment tools are increasingly used to inform bail, sentencing, and parole decisions. We examine New York City's stop-and-frisk program, and propose two new use cases for personalized risk assessments. First, we show that risk assessment tools can help police officers make considerably better real-time stop decisions. Second, we show that such tools can help audit past actions; in particular, we argue that a sizable fraction of police stops were conducted on the basis of little evidence, in possible violation of constitutional protections.

Suggested Citation

  • Sharad Goel & Justin M. Rao & Ravi Shroff, 2016. "Personalized Risk Assessments in the Criminal Justice System," American Economic Review, American Economic Association, vol. 106(5), pages 119-123, May.
    • Handle: RePEc:aea:aecrev:v:106:y:2016:i:5:p:119-23
    Note: DOI: 10.1257/aer.p20161028
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    References listed on IDEAS

    as
    1. Richard Berk & Lawrence Sherman & Geoffrey Barnes & Ellen Kurtz & Lindsay Ahlman, 2009. "Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learning," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 191-211, January.
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    Cited by:

    1. Xiaochen Hu & Xudong Zhang & Nicholas Lovrich, 2021. "Public perceptions of police behavior during traffic stops: logistic regression and machine learning approaches compared," Journal of Computational Social Science, Springer, vol. 4(1), pages 355-380, May.
    2. Eli Ben-Michael & D. James Greiner & Melody Huang & Kosuke Imai & Zhichao Jiang & Sooahn Shin, 2024. "Does AI help humans make better decisions? A methodological framework for experimental evaluation," Papers 2403.12108, arXiv.org.
    3. Stevenson, Megan T. & Doleac, Jennifer, 2019. "Algorithmic Risk Assessment in the Hands of Humans," IZA Discussion Papers 12853, Institute of Labor Economics (IZA).

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    More about this item

    JEL classification:

    • H76 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Other Expenditure Categories
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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