Impact of Risk Assessment on Judges’ Fairness in Sentencing Relatively Poor Defendants
UVA Law Faculty Affiliations
The increasing use of risk assessment algorithms in the criminal justice system has generated enormous controversy. Advocates emphasize that algorithms are more transparent, consistent, and accurate in predicting re-offending than judges’ unaided intuition, while skeptics worry that algorithms will increase racial and socioeconomic disparities in incarceration. Ultimately, however, judges make decisions—not algorithms. In the present study, real judges (n=340) with criminal sentencing experience participated in a controlled experiment to test whether the provision of risk assessment information interacts with a defendant’s socioeconomic class to influence sentencing decisions. Results revealed that risk assessment information reduced the likelihood of incarceration for relatively affluent defendants, but the same risk assessment information increased the likelihood of incarceration for relatively poor defendants. This finding held after controlling for the sex, race, political orientation, and jurisdiction of the judge. It appears that under some circumstances, risk assessment information can increase sentencing disparities.