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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Document Type

Article

Publication Date

3-2022

ISSN

0010-6151

Publisher

University of Connecticut School of Law

Language

en-US

Abstract

Jurisdictions are increasingly embracing the use of pretrial risk assessment algorithms as a solution to the problem of mass pretrial incarceration. Conversations about the use of pretrial algorithms in legal scholarship have tended to focus on their opacity, determinativeness, reliability, validity, or their (in)ability to reduce high rates of incarceration as well as racial and socioeconomic disparities within the pretrial system. This Article breaks from this tendency, examining these algorithms from a democratization of criminal law perspective. Using this framework, it points out that currently employed algorithms are exclusionary of the viewpoints and values of the racially marginalized communities most impacted by their usage, since these algorithms are often procured, adopted, constructed, and overseen without input from these communities.

This state of affairs should caution enthusiasm for the transformative potential of pretrial algorithms since they reinforce and entrench the democratic exclusion that members of these communities already experience in the creation and implementation of the laws and policies shaping pretrial practices. This democratic exclusion, alongside social marginalization, contributes to the difficulties that these communities face in contesting and resisting the political, social, and economic costs that pretrial incarceration has had and continues to have on them. Ultimately, this Article stresses that resolving this democratic exclusion and its racially stratifying effects might be possible but requires shifting power over pretrial algorithms toward these communities. Unfortunately, the actualization of this prescription may be unreconcilable with the aims sought by algorithm reformers, revealing a deep tension between the algorithm project and racial justice efforts.

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