Artificial intelligence at sentencing: when do algorithms perform well enough to replace humans?

Abstract

Artificial intelligence is currently supplanting the work of humans in many societal contexts. The purpose of this article is to consider the question of when algorithmic tools should be regarded as performing sufficiently well to replace human judgements and decision-making at sentencing. More precisely, the question as to which are the ethically plausible criteria for the comparative performance assessments of algorithms and humans is considered with regard to both risk assessment algorithms that are designed to provide predictions of recidivism and sentencing algorithms designed to determine sentences in individual criminal cases. It is argued, first, that the prima facie most obvious assessment criteria do not stand up to ethical scrutiny. Second, that ethically plausible criteria presuppose ethical theory on penal distribution which currently has not been sufficiently developed. And third, that the current lack of assessment criteria has comprehensive implications regarding when algorithmic tools should be implemented in criminal justice practice.