Algorithmic Risk Assessments and the Double-Edged Sword of Youth

Abstract

At sentencing, youth can be considered both a mitigating circumstance because of its association with diminished culpability and an aggravating circumstance because of its association with crime-risk. In theory, judges and parole boards can recognize this double-edged sword phenomenon and balance the mitigating and aggravating effects of youth. But when sentencing authorities rely on algorithmic risk assessments, a practice that is becoming increasingly common, this balancing process may never take place. Algorithmic risk assessments often place heavy weights on age in a manner that is not fully transparent – or, in the case of proprietary “black-box” algorithms, not transparent at all. For instance, our analysis of one of the leading black-box tools, the COMPAS Violent Recidivism Risk Score, shows that roughly 60% of the risk score it produces is attributable to age. We argue that this type of fact must be disclosed to sentencing authorities in an easily-interpretable manner so that they understand the role an offender’s age plays in the risk calculation. Failing to reveal that a stigmatic label such as “high risk of violent crime” is due primarily to a defendant’s young age could lead to improper condemnation of a youthful offender, especially given the close association between risk labels and perceptions of character and moral blameworthiness.

Keywords: Risk Assessment, Juvenile Justice, Double-Edged Sword, Sentencing, Algorithm