Algorithmic Risk Assessment in the Hands of Humans

Abstract

We evaluate the impacts of adopting algorithmic risk assessments in sentencing. We find that judges changed sentencing practices in response to the risk assessment, but that discretion played a large role in mediating its impact. Judges deviated from the recommendations associated with the algorithm in systematic ways, suggestive of alternative objectives at sentencing. As a result, risk assessment did not lead to detectable gains in terms of public safety or reduced incarceration rates. Using simulations, we show that strict adherence to the sentencing recommendations associated with the algorithm would have led to some benefits (a sharp reduction in incarceration) but also some costs (a slight increase in recidivism and an increase in relative sentences for the young). Discretion mitigated the costs at the expense of reducing the benefits.

Keywords: risk assessment, algorithms, sentencing

JEL Classification: K14