By ANNA MARIA BARRY-JESTER, BEN CASSELMAN and DANA GOLDSTEIN
This article discussed a new era of the criminal justice system, and in particular, the rise of using risk assessments (a tool that has assisted in other parts of the justice process) to help determine prison sentences of defendants. Risk assessments are tools that try to predict recidivism, which is a habitual disturbance of the law, or reoffending. Many states use these in their decisions about parole and bail, but Pennsylvania is ready to take another step that could present ethical complications: using risk assessments in actual sentencing. On one hand, this new proposal could help the system tremendously: state budgets can be more appropriately catered to keeping the most dangerous criminals behind bars while spending less on corrections facilities on those who will re-offend regardless. Furthermore, in theory, risk assessments would mitigate prejudice and bias against that human police officers, judges, and probation officers might hold subconsciously. However, on the other hand, this could lead down a slippery-slope of perhaps introducing even more unfair biases. Basing sentencing decisions on uncontrollable factors like race, socioeconomic status, sex, and age are morally unjust. Basing sentencing decisions on the statistical behavior of a previous group of individuals when analyzing one person’s case also may not be an ethical approach. The article utilizes a simulation to demonstrate how risk assessments would sort prisoners into low-risk and high-risk groups and either award or deny them parole based on their labels. It exemplifies the importance of finding a balance between the thresholds, considering that some are awarded parole and then reoffend, and some are denied parole but would not have reoffended. Yet, there are signs that risk assessments could provide a more precise insight with information that according to psychologists have around 10 percent more accuracy at predicting human behavior than experts without this tool. But just because predictions may be more factually correct does not mean that it is fair and ethically permissible to use during sentencing. There is another interactive activity that shows that risk assessments do not eliminate biases and may worsen the gap between minorities and the majority, and the lower class and the upper class. The solution developed by Richard Berk, a University of Pennsylvania statistician, was to sort offenders into 3 risk categories, thus corresponding to different supervision systems. The result was fairly successful: recidivism, especially repeat acts of violence, has fallen in the years since the establishment.
This article immediately caught my eye and I couldn’t wait to dive deeper into this topic. The idea of punishing individuals for crimes that might commit in the future is certainly intriguing, as is the growing ethical debate about the systems and tools involved. Many of the points made allowed me to expand on my thinking about the previous paper that I read by Danks with consequentialism versus deontology, and the varying measures of utility and prioritizations. All things considered, I learned a lot from this reading, and to me it was one of the most interesting by far!