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AI In Criminal Justice: Can Algorithms Decide Guilt?




Shravani Joshi, BA LLB, Yashwantrao Chavan Government Law College, Pune, Maharashtra

Madhura Kulkarni, BA LLB, Yashwantrao Chavan Government Law College, Pune, Maharashtra


ABSTRACT


This paper critically examines the integration of Artificial Intelligence (AI) into the criminal justice system, with a focus on its implications for fairness, transparency, and constitutional due process. AI technologies such as predictive policing, risk assessment tools, facial recognition, and crime mapping are increasingly deployed to enhance efficiency and data-driven decision-making in investigations and trials.

While these tools offer potential benefits including speed, accuracy, and reduced bias; their use also raises significant legal and ethical concerns. The “black box” nature of algorithms undermines the accused’s right to a fair trial and presumption of innocence by producing opaque, unchallengeable outcomes. Moreover, AI-driven surveillance and profiling pose risks to privacy and may reinforce systemic biases. This paper argues that while AI can serve as a powerful administrative aid in legal research, case management, and clerical functions, its role in core judicial decision-making must remain limited and transparent. The analysis concludes that AI should assist, but never replace, human judgment in criminal adjudication, emphasizing the need for regulatory safeguards, a “right to explanation,” and a human-centered approach to justice.


Keywords: Artificial Intelligence, Criminal Justice, Risk assessment tools, Black box problem, Human Demeanour, Algorithmic Transparency.



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.

 

Disclaimer:

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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