Predictive Algorithms in Justice Systems and the Limits of Tech-Reformism

Pam Ugwudike

doi:10.5204/ijcjsd.2189

Abstract

Data-driven digital technologies are playing a pivotal role in shaping the global landscape of criminal justice across several jurisdictions. Predictive algorithms, in particular, now inform decision making at almost all levels of the criminal justice process. As the algorithms continue to proliferate, a fast-growing multidisciplinary scholarship has emerged to challenge their logics and highlight their capacity to perpetuate historical biases. Drawing on insights distilled from critical algorithm studies and the digital sociology scholarship, this paper outlines the limits of prevailing tech-reformist remedies. The paper also builds on the interstices between the two scholarships to make a case for a broader structural framework for understanding the conduits of algorithmic bias.

Highlights

Digital technological innovations such as predictive algorithms are transforming the infrastructure of private and public sector services across several jurisdictions
This paper focuses on the predictive algorithms1 that are increasingly applied in justice systems for crime risk prediction
It makes an original contribution by drawing on the tools to, (1) outline the limits of prevailing tech-reformist remedies, and (2) demonstrate how poorly suited they are to the task of mitigating or remedying algorithmic bias

Summary

Introduction

Digital technological innovations such as predictive algorithms are transforming the infrastructure of private and public sector services across several jurisdictions. This paper utilises conceptual tools distilled from two scholarships—critical algorithm studies (CAS) and digital sociology (DS)—to address the paucity of insights and unravel the underpinning tensions It makes an original contribution by drawing on the tools to, (1) outline the limits of prevailing tech-reformist remedies, and (2) demonstrate how poorly suited they are to the task of mitigating or remedying algorithmic bias. This paper begins with an overview of how predictive algorithms in justice systems operate and some of the key challenges, focusing on predictive policing and risk assessment algorithms It proceeds with a description of conceptual tools from the CAS and DS scholarships, which are useful for unravelling the broad structural roots and implications of the challenges. The paper, inspired by the aforementioned conceptual tools, provides a structural framework for addressing such bias

Predictive Algorithms in Justice Systems

Remedying Algorithmic Bias

Findings

Conclusion