Risk-assessment tools in the U.S. Criminal Justice System: Construction, Diffusion, and Uses

• In Event: 033 - Section on Crime, Law, and Deviance Roundtable Session and Business Meeting
  In Refereed Roundtable 60min: Table 18. Procedures and Justice 2

Abstract

One of the most striking innovations in the criminal justice system during the past thirty years has been the introduction of actuarial methods – statistical models and software programs – designed to help judges and prosecutors assess the risk of criminal offenders. Predictive algorithms are currently used in four major areas of the U.S. criminal justice system: pretrial and bail, sentencing, probation and parole, and juvenile justice. These algorithms consider a small number of variables about a defendant – either connected to her or his criminal history (previous offenses, failure to appear in court, violent offenses, etc.) or socio- demographic characteristics (age, sex, employment status, drug history, etc.) – in an effort to predict a defendant’s risk of recidivism or their likelihood to fail to appear in court if they are let out on bail. Advocates for increased use of actuarial instruments highlight their potential to automate and standardize decision-making processes by considering relevant risk factors. This article argues instead that there is an important gap between the normative goals and the actual consequences of data-driven sentencing.

Author

• Angele Christin, Data & Society Research Institute