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Making a Murderer –- How risk assessment tools may produce rather than predict criminal behavior

Khosrowi, Donal and van Basshuysen, Philippe (2023) Making a Murderer –- How risk assessment tools may produce rather than predict criminal behavior. [Preprint]

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Abstract

Risk assessment tools, such as COMPAS, may not only predict defendants’ risk of recidivism, but may themselves causally affect recidivism outcomes. 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.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Khosrowi, Donaldonal.khosrowi@durham.ac.uk
van Basshuysen, Philippep.c.van-basshuysen@lse.ac.uk0000-0003-1947-9309
Keywords: performativity; risk assessment; recidivism; algorithmic fairness; explainability
Subjects: Specific Sciences > Artificial Intelligence > AI and Ethics
Specific Sciences > Computer Science
General Issues > Ethical Issues
General Issues > Science and Policy
General Issues > Technology
General Issues > Values In Science
Depositing User: Mr. Philippe van Basshuysen
Date Deposited: 31 Aug 2023 15:52
Last Modified: 31 Aug 2023 15:52
Item ID: 22468
Subjects: Specific Sciences > Artificial Intelligence > AI and Ethics
Specific Sciences > Computer Science
General Issues > Ethical Issues
General Issues > Science and Policy
General Issues > Technology
General Issues > Values In Science
Date: 31 July 2023
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/22468

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