The Compassionate Computer: Algorithms, Sentencing, and Mercy
In: Principled Sentencing and Artificial Intelligence (working title) J.V. Roberts & J. Ryberg eds., OUP, Forthcoming
33 Pages Posted: 4 Nov 2020
Date Written: September 14, 2020
Sentencing scholarship largely neglects the possibility of applying algorithms to mercy. This doesn’t come as a surprise: Is there any greater contradiction than between algorithmic decision-making and the compassionate, human and interpersonal nature of mercy? Such polarity brings some theorists and policy makers to reject algorithm-based sentencing altogether. In this chapter, we offer a preliminary attempt at integrating mercy within algorithmic sentencing. First, we distinguish between two main concepts of mercy – justice and pure – and different types of algorithms – deductive and inductive. Second, we argue: (a) As long as justice mercy can be reduced to a proportionality-related calculus (e.g., extra harsh suffering) it can be introduced through a deductive algorithm; (b) Pure mercy, being unpredictable, and deviating from justice, can be incorporated mainly through an inductive algorithm. This is true, at least to some extent, even for theories that permit deviation from equality when exercising mercy.
Keywords: sentencing, mercy, algorithms, proportionality, compassionate release, inductive/deductive algorithms
Suggested Citation: Suggested Citation