The Jurisprudence of Big Data: Legal Limits of Predictive Analytics in Criminal Justice Risk Assessment Models

Authors

    Katarzyna Lewandowska Faculty of Law and Administration, University of Warsaw, Warsaw, Poland
    Lukas Reinhardt * Institute of Political Science, Humboldt University of Berlin, Berlin, Germany lukas.reinhardt@hu-berlin.de
    Daniel Whitmore Department of Political Science, University of Michigan, Ann Arbor, USA

Keywords:

Predictive Justice, Algorithmic Governance, Criminal Justice, Risk Assessment, Constitutional Law, Big Data, Artificial Intelligence, Legal Theory

Abstract

The rapid integration of predictive analytics into criminal justice systems has transformed the architecture of legal decision-making by introducing algorithmic risk assessment tools into pre-trial processes, sentencing, parole, probation, and policing. While these technologies promise increased efficiency, consistency, and anticipatory capacity, they simultaneously generate profound jurisprudential and constitutional challenges. This article offers a comprehensive narrative review and descriptive–analytical examination of the theoretical foundations, technical architecture, and normative consequences of predictive criminal justice. Drawing upon interdisciplinary scholarship in law, criminology, data science, and political theory, the study traces the shift from classical legal rationality toward algorithmic governance and evaluates its implications for core legal principles. The analysis demonstrates that predictive systems fundamentally destabilize the principles of legality, due process, equality before the law, and the presumption of innocence by substituting probabilistic forecasting for individualized legal judgment. Moreover, structural bias, feedback amplification, and algorithmic opacity undermine procedural fairness and intensify social inequality, particularly for marginalized populations. The article further argues that predictive governance redistributes legal authority from courts to opaque technical systems and private actors, eroding democratic accountability and judicial autonomy. Through comparative constitutional analysis, the study highlights divergent regulatory responses across jurisdictions and emphasizes the urgent need for a renewed constitutional framework capable of constraining algorithmic power. Ultimately, the article contends that the legal limits of predictive criminal justice are anchored in the normative foundations of constitutionalism itself, requiring a reassertion of human judgment, transparency, and rights-based adjudication in the governance of emerging technologies.

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Published

2023-10-01

Submitted

2023-08-16

Revised

2023-09-10

Accepted

2023-09-23

How to Cite

Lewandowska, K., Reinhardt, L., & Whitmore, D. (2023). The Jurisprudence of Big Data: Legal Limits of Predictive Analytics in Criminal Justice Risk Assessment Models. Legal Studies in Digital Age, 2(4), 48-60. https://jlsda.com/index.php/lsda/article/view/332

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