Predicting risk in criminal procedure: actuarial tools, algorithms, AI and judicial decision-making

Abstract

Risk assessments are conducted at a number of decision points in criminal procedure including in bail, sentencing and parole as well as in determining extended supervision and continuing detention orders of high-risk offenders. Such risk assessments have traditionally been the function of the human discretion and intuition of judicial officers, based on clinical assessments, framed by legislation and common-law principles, and encapsulating the concept of individualised justice. Yet, the progressive technologisation of criminal procedure is witnessing the incursion of statistical, data-driven evaluations of risk. Human judicial evaluative functions are increasingly complemented by a range of actuarial, algorithmic, machine learning and Artificial Intelligence (AI) tools that purport to provide accurate predictive capabilities and objective, consistent risk assessments. But ethical concerns have been raised globally regarding algorithms as proprietary products with in-built statistical bias as well as the diminution of judicial human evaluation in favour of the machine. This article focuses on risk assessment and what happens when decision-making is delegated to a predictive tool. Specifically, this article scrutinises the inscrutable proprietary nature of such risk tools and how that may render the calculation of the risk score opaque and unknowable to both the offender and the court.