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


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.

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Published: 2022-03-01
Pages:85 to 99
Section:Part 1: Digital (in)Justices
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How to Cite
Ugwudike , P. . (2022) “Predictive Algorithms in Justice Systems and the Limits of Tech-Reformism”, International Journal for Crime, Justice and Social Democracy, 11(1), pp. 85-99. doi: 10.5204/ijcjsd.2189.

Author Biography

University of Southampton
 United Kingdom

Dr Pamela Ugwudike is an Associate Professor of Criminology and Director of Research at the Department of Sociology, Social Policy and Criminology, University of Southampton. She is also a Fellow of the Alan Turing Institute (the UK’s national institute for data science and artificial intelligence) and a co-Editor-in-Chief of Criminology and criminal Justice Journal, the flagship Journal of the British Society of Criminology.  Her research considers the ethical and social implications of Artificial Intelligence (AI) systems, with a focus on the data-driven technologies (such as risk prediction and online social networking algorithms) that structure knowledge production and inform criminal justice policy.