Machine learning and forensic risk assessment: new frontiers

• Published in: The journal of forensic psychiatry & psychology Vol. 31; no. 4; pp. 571 - 581
• Main Authors: Spivak, Benjamin L., Shepherd, Stephane M.
• Format: Journal Article
• Language: English
• Published: Abingdon Routledge 03-07-2020; Taylor & Francis Ltd
• Subjects: Academic disciplines; Cognitive style; Computer science; Experts; Forensic psychology; Machine learning; Offending; Psychological assessment; Risk assessment
• ISSN: 1478-9949; 1478-9957
• DOI: 10.1080/14789949.2020.1779783

Advanced approaches to predicting offending are increasingly transpiring without the forensic psychology discipline's involvement - an area that it has piloted and influenced for many decades. Computer science experts have built an impressive decade-long literature base on risk assessment - a technical literature that is not only progressing at a fast pace, but appears to function independently, for the most part, from the forensic risk assessment literature. This paper outlines the potential utility of machine learning approaches and the broader 'algorithmic culture', for forensic risk assessment, and the implications their use (and non-use) may have for the discipline.