scholarly journals The Trouble with Using Risk Assessment Instruments to Quantify the Chance of Future Offending

2021 ◽  
Vol 13 (21) ◽  
pp. 11624
Author(s):  
Tim Goddard
Keyword(s):  
Risk Assessment ◽  
Justice System ◽  
Criminal History ◽  
People Of Color ◽  
Assessment Instruments ◽  
Past Behavior ◽  
Decision Points ◽  
Actuarial Risk Assessment ◽  
Actuarial Risk ◽  
Radical Shift

Risk assessments in carceral settings have proliferated in recent decades and are now prominent in numerous states and regions. A ubiquitous variety is actuarial risk assessment instruments that are used on children and adults to predict their future chance for misconduct (e.g., recidivism) in several vital decision points in carceral processing (e.g., pretrial confinement). These instruments rely on information about past behavior (e.g., criminal history) and an understanding of offending (e.g., antisocial personality) that is thought to be neutral, reliable, and enjoys predictive validity. However, it will be argued that when justice system personnel assess the chance of unwanted behavior in the future, several risk domains are differentially prevalent and more frequently experienced by some groups. Much of this disparity is caused by, or due to, forces external to those being assessed, for instance, inequitable social and economic conditions and inequitable decisions by justice personnel to arrest, charge, or sentence people of color. As such, risk assessment instruments inevitably and disproportionately mark some groups of people as a higher risk to violate rules, conditions, orders, or laws. Consequently, risk assessment instruments systematically disfavor disadvantage, and by inference, favor advantage, leading to the need for a radical shift in the taxonomy of classifying risk for future misconduct.

Evidence-Based Sentencing

Criminology ◽  
2021 ◽  
Author(s):  
James C. Oleson
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Measures ◽  
Criminal History ◽  
Community Safety ◽  
Assessment Instruments ◽  
Evidence Based ◽  
Criminogenic Needs ◽  
Actuarial Risk ◽  
Using Data

The evidence-based practice (EBP) movement can be traced to a 1992 article in the Journal of the American Medical Association, although decision-making with empirical evidence (rather than tradition, anecdote, or intuition) is obviously much older. Neverthless, for the last twenty-five years, EBP has played a pivotal role in criminal justice, particularly within community corrections. While the prediction of recidivism in parole or probation decisions has attracted relatively little attention, the use of risk measures by sentencing judges is controversial. This might be because sentencing typically involves both backward-looking decisions, related to the blameworthiness of the crime, as well as forward-looking decisions, about the offender’s prospective risk of recidivism. Evidence-based sentencing quantifies the predictive aspects of decision-making by incorporating an assessment of risk factors (which increase recidivism risk), protective factors (which reduce recidivism risk), criminogenic needs (impairments that, if addressed, will reduce recidivism risk), the measurement of recidivism risk, and the identification of optimal recidivism-reducing sentencing interventions. Proponents for evidence-based sentencing claim that it can allow judges to “sentence smarter” by using data to distinguish high-risk offenders (who might be imprisoned to mitigate their recidivism risk) from low-risk offenders (who might be released into the community with relatively little danger). This, proponents suggest, can reduce unnecessary incarceration, decrease costs, and enhance community safety. Critics, however, note that risk assessment typically looks beyond criminal conduct, incorporating demographic and socioeconomic variables. Even if a risk factor is facially neutral (e.g., criminal history), it might operate as a proxy for a constitutionally protected category (e.g., race). The same objectionable variables are used widely in presentence reports, but their incorporation into an actuarial risk score has greater potential to obfuscate facts and reify underlying disparities. The evidence-based sentencing literature is dynamic and rapidly evolving, but this bibliography identifies sources that might prove useful. It first outlines the theoretical foundations of traditional (non-evidence-based) sentencing, identifying resources and overviews. It then identifies sources related to decision-making and prediction, risk assessment logic, criminogenic needs, and responsivity. The bibliography then describes and defends evidence-based sentencing, and identifies works on sentencing variables and risk assessment instruments. It then relates evidence-based sentencing to big data and identifies data issues. Several works on constitutional problems are listed, the proxies problem is described, and sources on philosophical issues are described. The bibliography concludes with a description of validation research, the politics of evidence-based sentencing, and the identification of several current initiatives.

scholarly journals Precision of actuarial risk assessment instruments

2007 ◽  
Vol 190 (S49) ◽  
pp. s60-s65 ◽  
Author(s):  
Stephen D. Hart ◽  
Christine Michie ◽  
David J. Cooke
Keyword(s):  
Risk Assessment ◽  
Individual Risk ◽  
Assessment Instruments ◽  
Individual Level ◽  
Risk Estimates ◽  
Extreme Risk ◽  
Actuarial Risk Assessment ◽  
Degree Of Certainty ◽  
Actuarial Risk ◽  
The Individual

BackgroundActuarial risk assessment instruments (ARAIs) estimate the probability that individuals will engage in future violence.AimsTo evaluate the ‘margins of error’ at the group and individual level for risk estimates made using ARAIs.MethodAn established statistical method was used to construct 95% CI for group and individual risk estimates made using two popular ARAIs.ResultsThe 95% CI were large for risk estimates at the group level; at the individual level, they were so high as to render risk estimates virtually meaningless.ConclusionsThe ARAIs cannot be used to estimate an individual's risk for future violence with any reasonable degree of certainty and should be used with great caution or not at all. In theory, reasonably precise group estimates could be made using ARAIs if developers used very large construction samples and if the tests included few score categories with extreme risk estimates.

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