Public safety assessment

• DOI: http://doi.org/10.1111/1745-9133.12481
• Published date: 01 May 2020
• Author: Matthew DeMichele,Peter Baumgartner,Kelle Barrick,Michael Wenger,Megan Comfort
• Date: 01 May 2020

DOI: 10.1111/1745-9133.12481

ORIGINAL ARTICLE

RISK ASSESSMENT

Public safety assessment

Predictive utility and differential prediction by race in Kentucky

Matthew DeMichele Peter Baumgartner Michael Wenger

Kelle Barrick Megan Comfort

RTI International

Correspondence

MatthewDeMichele, Center for Courts amd

Corrections Research,3040 E. Cor nwallis

Road,Research Triangle Park, NC 27709-2194.

Email:mdemichele@r ti.org

Fundinginformation

Lauraand John Ar nold Foundation,

Grant/AwardNumber: 0215129

Research Summary: Weassess the predictive validity and

differential prediction by race of one pretrial risk assess-

ment, the Public Safety Assessment (PSA). The PSA was

developed with support from the Laura and John Arnold

Foundation (LJAF) to reduce the burden placed on vulner-

able populations at the front end of the criminal justice sys-

tem. The growing and disparate use of incarceration is one

of the most pressing social issues facing the United States.

The implementation of risk assessments has provided fuel

for both sides of the reform debate with proponents arguing

that the use of these assessments offers a policy mechanism

to alleviate populations and bias. Risk assessment critics,

however, argue that the use of the assessments exacerbates

bias and does not improve decision-making. By examin-

ing a statewide data set from Kentucky (N=164,597), we

found the PSA to have predictive validity measures in line

with what are generally accepted within the criminal justice

field. The differences we found indicate the PSA scores for

failure to appear (FTA) are moderated by race, but these

differences do not lead to disparate impact.

Policy Implications: We point to data limitations and the

need for localized risk assessment studies, and we empha-

size that risk assessments are decision-making tools that

require ongoing refinement. Risk assessment developers,

opponents, and proponents would do better to focus on

Criminology & Public Policy. 2020;19:409–431. wileyonlinelibrary.com/journal/capp © 2020 American Society of Criminology 409

410 DEMICHELE ET AL.

the reality of risk assessments as probabilistic models. The

results of these assessments cannot predict with certainty,

and they are not inherently biased. Rather, criminologists

and policy makers need to understand the uncertainty that

comes with any predictive model.

Pretrial populations are a large and growing contributor of mass incarceration. According to the

Bureau of Justice Statistics (BJS), the proportion of jail populations that are unconvicted has increased

from 50% in 1985 to nearly 65% in 2017 (Zeng, 2019). Although jail populations have declined to

approximately 745,000 in 2017 since their peak in 2008 from slightly more than 785,000 (Zeng, 2019),

BJS estimated that nearly 95% of the growth in jail populations since 2000 was a result of the increase

in the proportion of those held in jails that are unconvicted (Minton & Zeng, 2015). The pretrial phase

is often said to be the most consequential in the criminalizing process because it is related to several

legal and personal outcomes (Sacks & Ackerman, 2014). During pretrial, individuals are legally inno-

cent and have a right to be released, but many jails are filled with pretrial populations because judges

have the ability to detain individuals as a result of concerns of flight or safety (United States v. Salerno,

1985).

Judges make decisions about the release or detention of someone on a regular basis. For the most

part, pretrial release decisions are based on the seriousness of the crime and on criminal history

(Gottfredson & Gottfredson, 1988; Spohn & Holleran, 2000), but these decisions are often made

quickly, with limited information, and rely on predetermined bond schedules. Pretrial release deci-

sions are especially challenging because judges grapple with balancing public safety and protecting

the community with the inherent rights of the accused.

The reliance on financial conditions for pretrial release has “almost from its inception, been the

subject of dissatisfaction” (Ares, Rankin, & Sturz, 1963, p. 67). The nature of these concerns has been

focused on the fairness by which pretrial release decisions are made and the potential for disparate

treatment of the poor and vulnerable (e.g., Beeley, 1927; Foote, 1954). Pretrial detention is associated

with a higher likelihood of conviction and with longer terms of incarceration, and it has the potential

to destabilize families (Sacks & Ackerman, 2014).1The speed by which pretrial release decisions

are made often results in legal actors having incomplete information and a high amount of discretion

in which two criteria are the basis for release decisions: public safety and likelihood of returning to

court (Goldkamp & Gottfredson, 1985; Mayson, 2018; United States v. Salerno, 1985). Furthermore,

the legal rules for pretrial release allow for judges to consider extralegal factors such as employment,

community ties, and marital status when deciding whether to release someone (Goldkamp & Vilcica,

2009). These challenges to pretrial release are compounded by the reliance on financial conditions or

bail as a requirement of release, with bail having an enduring history of negative impacts for the poor

and communities of color (e.g., Ares et al., 1963; Demuth, 2003).

Recognizing the inherent challenges in pretrial release decisions, there has been increased develop-

ment and use of pretrial risk assessments (Pretrial Justice Institute, 2017). Pretrial risk assessments are

developed to identify the likelihood that defendants will remain crime free and that they will return

to court. The Pretrial Justice Institute (2017) estimated that approximately 25% of jurisdictions use an

actuarial risk assessment, which is an increase from just 10% in 2013. These tools are emerging among

vocal opposition about predictive utility and whether they contribute to racial disparities, with critics

arguing that risk assessments are reliant on group-based patterns that will lead to unfair treatment of