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Forecasting Guilt: Dangerousness, Algorithmic Prediction, And The Constitutional Limits Of Preventive Justice

Jul 16
2 min read



Animesh Singh, Assistant Professor, Law, Babu Banarasi Das University


ABSTRACT


Criminal justice systems are shifting from a reactive model, which punishes conduct already committed, toward a preventive model, which restrains liberty on the basis of anticipated future conduct. This shift is visible in clinical and actuarial risk assessment, in AI-assisted predictive policing and algorithmic sentencing tools, and in long-standing preventive detention regimes. This paper asks whether dangerousness can be predicted with sufficient psychological and scientific reliability to justify depriving a person of liberty before any offence occurs; whether algorithmic decision-making reduces or reproduces human bias in that prediction; whether preventive detention is constitutionally compatible with prediction-based justice; and what safeguards should govern AI-assisted predictive justice. Adopting a doctrinal, comparative, and interdisciplinary methodology centred on India, with comparative reference to the United States and the United Kingdom, the paper traces the psychological science of violence prediction, the architecture and documented biases of algorithmic risk-assessment tools, and India's existing statutory model of preventive detention under the National Security Act 1980, the Unlawful Activities (Prevention) Act 1967, and the Conservation of Foreign Exchange and Prevention of Smuggling Activities Act 1974, read against Article 21 and Article 22 jurisprudence from A.K. Gopalan to Puttaswamy. It argues that dangerousness is an inherently probabilistic construct that cannot, by itself, constitute an independent basis for depriving personal liberty; that artificial intelligence enhances predictive capacity without eliminating the psychological uncertainty and systemic bias underlying dangerousness assessment; and that predictive justice consequently requires a constitutional framework anchored in criminal psychology, due process, and proportionality rather than in confidence borrowed from computation.


Keywords: Dangerousness; Criminal Psychology; Predictive Policing; Preventive Detention; Algorithmic Risk Assessment; Constitutional Law; Due Process.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

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The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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