Algorithmic risk assessments and the double-edged sword of youth

Behav Sci Law. 2018 Sep;36(5):638-656. doi: 10.1002/bsl.2384.

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.

MeSH terms

  • Adolescent
  • Age Factors
  • Algorithms
  • Criminal Psychology / instrumentation*
  • Female
  • Humans
  • Judicial Role*
  • Juvenile Delinquency* / legislation & jurisprudence
  • Juvenile Delinquency* / psychology
  • Male
  • Risk Assessment / methods*
  • Risk Factors
  • Supreme Court Decisions
  • United States