Making a murderer

How Risk Assessment Tools May Produce Rather Than Predict Criminal Behavior

authored by

Donal Khosrowi, Philippe van Basshuysen

Abstract

Algorithmic risk assessment tools, such as COMPAS, are increasingly used in criminal justice systems to predict the risk of defendants to reoffend in the future. This paper argues that these tools may not only predict recidivism, but may themselves causally induce recidivism through self-fulfilling predictions. We argue that such “performative” effects can yield severe harms both to individuals and to society at large, which raise epistemic-ethical responsibilities on the part of developers and users of risk assessment tools. To meet these responsibilities, we present a novel desideratum on algorithmic tools, called explainability-in-context, which requires clarifying how these tools causally interact with the social, technological, and institutional environments they are embedded in. Risk assessment practices are thus subject to high epistemic standards, which haven’t been sufficiently appreciated to date. Explainability-in-context, we contend, is a crucial goal to pursue in addressing the ethical challenges surrounding risk assessment tools.

Organisation(s)

Institute of Philosophy
Centre for Ethics and Law in the Life Sciences

Type

Article

Journal

AMERICAN PHILOSOPHICAL QUARTERLY

Volume

61

Pages

309-325

No. of pages

17

ISSN

0003-0481

Publication date

01.10.2024

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Philosophy

Sustainable Development Goals

SDG 16 - Peace, Justice and Strong Institutions

Electronic version(s)

https://doi.org/10.5406/21521123.61.4.02 (Access: Closed)