Parole Algorithm Debate Continues

The debate over the use of algorithms to “help make decisions about whom to release before trial, whom to release from prison on parole or who receives rehabilitative services” continues. Zhiyuan Lin et al. have this op-ed in the WaPo defending the value of using algorithms.

More than 60 years of research suggests that statistical algorithms are better than unaided human judgment at predicting such outcomes. In 2018, that body of research was questioned by a high-profile study published in the journal Science Advances, which found that humans and algorithms were about equally as good at assessing who will reoffend. But when we attempted to replicate and extend that recent study, we found something different: Algorithms were substantially better than humans when used in conditions that approximate real-world criminal justice proceedings.

No doubt the authors of the study criticized here will reply with a defense of their work. But there is another reason to be skeptical of decision by algorithm.

At the end of the article, the authors note that “policymakers may decide that risk simply should not factor into some legal decisions.” They cite New York’s bail law, which they call “groundbreaking” and a growing number of New Yorkers call disastrous.

It certainly is a valid and important point, though, that in many contexts risk of recidivism should not be the sole criterion. For release on parole, particularly, we should also consider whether the time served to date is adequate punishment for the crime the perpetrator chose to commit. In many murder cases the answer will always be “no,” and that renders the risk of recidivism irrelevant.