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Admissibility And Reliability Of AI-Generated Evidence In Indian Criminal Trials: Challenges To Proof, Authenticity And Legal Liability




Bharti Kataria

Prof. (Dr.) Ashwani Kumar Dwivedi


ABSTRACT


The growing integration of Artificial Intelligence (AI) into criminal investigations has introduced a new category of evidence generated through algorithmic processes, including facial recognition systems, predictive analytics, and automated forensic tools. While such AI-generated evidence enhances efficiency and investigative capabilities, it raises significant concerns regarding its admissibility and reliability in criminal trials. In India, the existing evidentiary framework under the Bharatiya Sakshya Adhiniyam, 2023, primarily addresses electronic and digital records but does not specifically account for the complexities associated with AI-generated outputs.


This paper critically examines the challenges posed by the use of AI-generated evidence in Indian criminal proceedings, particularly with respect to proof, authenticity, and legal liability. It highlights issues such as algorithmic opacity, bias in training data, lack of transparency, and the risk of manipulation, including the use of deepfakes. The study further explores the implications of relying on such evidence for the right to a fair trial and the presumption of innocence.


By analysing statutory provisions, judicial approaches, and comparative international practices, the paper argues that the current legal framework is insufficient to address the unique challenges posed by AI. It emphasises the need for clear guidelines on admissibility, enhanced standards for reliability, and a well-defined framework for fixing liability. The paper concludes by recommending legal and policy reforms to ensure that the use of AI in criminal trials aligns with principles of fairness, accountability, and justice.


Keywords: Artificial Intelligence (AI), AI-Generated Evidence, Criminal Trials, Admissibility of Evidence, Reliability, Bharatiya Sakshya Adhiniyam, 2023, Digital Evidence, Algorithmic Bias, Deepfakes, Legal Liability, Fair Trial.



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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