Using algorithms to address trade-offs inherent in predicting recidivism.

Although risk assessment has increasingly been used as a tool to help reform the criminal justice system, some stakeholders are adamantly opposed to using algorithms. The principal concern is that any benefits achieved by safely reducing rates of incarceration will be offset by costs to racial justice claimed to be inherent in the algorithms themselves. But fairness trade-offs are inherent to the task of predicting recidivism, whether the prediction is made by an algorithm or human.

Age, risk assessment, and sanctioning: Overestimating the old, underestimating the young.

While many extoll the potential contribution of risk assessment to reducing the human and fiscal costs of mass incarceration without increasing crime, others adamantly oppose the incorporation of risk assessment in sanctioning. The principal concern is that any benefits in terms of reduced rates of incarceration achieved through the use of risk assessment will be offset by costs to social justice-which are claimed to be inherent in any risk assessment process that relies on variables for which offenders bear no responsibility, such as race, gender, and age. Previous research has addressed the variables of race and gender.

Gender, risk assessment, and sanctioning: The cost of treating women like men.

Increasingly, jurisdictions across the United States are using risk assessment instruments to scaffold efforts to unwind mass incarceration without compromising public safety. Despite promising results, critics oppose the use of these instruments to inform sentencing and correctional decisions. One argument is that the use of instruments that include gender as a risk factor will discriminate against men in sanctioning.

Predicting recidivism with the Psychological Inventory of Criminal Thinking Styles (PICTS) in community-supervised male and female federal offenders.

Higher order scores derived from the Psychological Inventory of Criminal Thinking Styles (PICTS; Walters, 1995) have been found to predict recidivism in released prison inmates with effect sizes in the low-moderate to medium range. The current study sought to determine whether the PICTS is capable of predicting general recidivism in a sample of 81,881 male and 14,519 female offenders on federal probation or supervised release. Results indicated that the PICTS General Criminal Thinking, Proactive, and Reactive scores and 6 of the 7 thinking style scales predicted recidivism in follow-ups of 6 or more months, 12 or more months, and 24 or more months with effect sizes in the low-moderate to medium range.

PCRA revisited: Testing the validity of the Federal Post Conviction Risk Assessment (PCRA).

The Post Conviction Risk Assessment (PCRA) was developed for use in the U.S. Probation System in 2009.

Evidence for risk estimate precision: implications for individual risk communication.

Actuarial risk assessment instruments using well-established predictor variables measured at the individual level (e.g., age, criminal history, psychopathy) discriminate well between recidivists and non-recidivists across diverse samples.

The federal Post Conviction Risk Assessment (PCRA): a construction and validation study.

Offender assessment has been and remains the cornerstone of effective community supervision. This article presents the development of and tests the predictive validity of a 4th-generation risk assessment instrument designed for U.S.

The systemic model of crime and institutional efficacy: an analysis of the social context of offender reintegration.

The systemic model of crime has received considerable empirical attention from criminologists; yet, an often-neglected component of the theoretical framework is the role of social institutions as a source of both formal and informal social control. Accordingly, the current study builds on recent research that considers the importance of institutional strength for the reduction of criminal behavior; in particular, the authors assess the impact of social-structural characteristics on the treatment program integrity (i.e.