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Open risk assessment.

Brandon L Garrett1,2, Megan Stevenson3

  • 1Duke University School of Law, Durham, NC, 27708, USA.

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|March 27, 2020
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Summary
This summary is machine-generated.

Criminal justice risk assessment tools lack transparency. Key assumptions and validation data for the federal First Step Act risk tool are inadequately supported, hindering open practices.

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Area of Science:

  • Criminal Justice
  • Public Policy
  • Data Science

Background:

  • Criminal justice systems increasingly adopt evidence-informed practices like risk assessment instruments.
  • Open science practices are not standard in developing tools for law enforcement, judges, and probation officers.
  • Lack of transparency in risk assessment tool development is a growing concern.

Purpose of the Study:

  • To examine the transparency and evidence base of risk assessment tools in criminal justice.
  • To evaluate the assumptions and validation data of the federal risk assessment tool used in prisons under the First Step Act.
  • To highlight the importance of open science in the development of criminal justice tools.

Main Methods:

  • Analysis of the development and implementation of risk assessment tools.
  • Review of transparency in scientific research and data accessibility for criminal justice tools.
  • Critical evaluation of the assumptions and validation data for the First Step Act risk assessment tool.

Main Results:

  • The development of criminal justice risk assessment tools often lacks transparency and public scrutiny.
  • Key assumptions and policy choices in the federal First Step Act risk assessment tool are not verifiable or are inadequately supported.
  • The validation data used in the federal tool is insufficient.

Conclusions:

  • The federal risk assessment tool under the First Step Act falls short of being a model for open risk assessment.
  • Greater transparency and adherence to open science practices are needed in the development of criminal justice tools.
  • Inadequate support for assumptions and validation data raises concerns about the reliability and fairness of the tool.