AI-Generated Evidence and the Indian Criminal Process: Challenges of Reliability and Admissibility
DOI :
https://doi.org/10.5281/zenodo.23233479Mots-clés :
Digital Forensics, Admissibility, Deepfakes, Bharatiya Sakshya Adhiniyam 2023, Electronic Evidence, Artificial IntelligenceRésumé
Artificial intelligence has transformed the evidentiary environment of criminal justice. Audio, video, images, documents and text can now be generated or altered with a degree of realism that makes ordinary visual or auditory inspection increasingly unreliable. India’s new evidence framework, the Bharatiya Sakshya Adhiniyam, 2023 (BSA), recognises electronic and digital records while imposing specific safeguards concerning their source, integrity, certification and hash values. The Supreme Court’s decision in Pune Bar Association v Union of India (2026) has upheld the constitutional validity of Section 63(4) and expressly recognised the heightened risks created by artificial intelligence and deepfakes. This article argues that admissibility, authenticity, reliability and probative weight must nevertheless remain analytically distinct. A technically compliant certificate can establish important aspects of provenance and integrity without establishing that an AI-generated representation is truthful, historically accurate or attributable to the person against whom it is tendered. The article examines synthetic media, AI enhancement, voice cloning, generated documents, algorithmic identification and machine-assisted forensic analysis. It analyses Sections 39, 61, 62 and 63 of the BSA, the relationship between the new regime and the Supreme Court’s Section 65B jurisprudence, and the fair-trial implications of opaque or insufficiently testable AI processes. It proposes a five-stage AI Evidence Reliability and Admissibility Test based on provenance, integrity, methodological reliability, contextual attribution and independent corroboration. The article concludes that Indian courts should neither exclude digital evidence merely because AI was involved nor presume that technical authenticity establishes truth. A calibrated, process-sensitive approach is required to preserve both technological utility and the presumption of innocence.
Téléchargements
Références
Anvar P.V. v P.K. Basheer, (2014) 10 SCC 473.
Arjun Panditrao Khotkar v Kailash Kushanrao Gorantyal, (2020) 7 SCC 1.
Bharatiya Nagarik Suraksha Sanhita, 2023, Act No. 46 of 2023.
Bharatiya Sakshya Adhiniyam, 2023, Act No. 47 of 2023.
Department-related Parliamentary Standing Committee on Home Affairs. (2023). 246th Report on the Bharatiya Sakshya Bill, 2023. Parliament of India.
Information Technology Act, 2000, Act No. 21 of 2000.
Ministry of Home Affairs. (2026). New Criminal Laws and implementation materials. Government of India.
Pune Bar Association v Union of India, W.P. (C) No. 599 of 2026, decided 22 May 2026 (Supreme Court of India).
R v B, 2024 SCC OnLine Mad 6084.
Shafhi Mohammad v State of Himachal Pradesh, (2018) 2 SCC 801.
State (NCT of Delhi) v Navjot Sandhu, (2005) 11 SCC 600.
Supreme Court of India. (2025). White Paper on Artificial Intelligence and Judiciary. Centre for Research and Planning, Supreme Court of India.
Supreme Court of India. (2026). National Conference on Judicial Process Re-engineering and Digital Transformation: Press releases and proceedings, 11–12 April 2026.
The Constitution of India, 1950.
Vikram Singh v State of Punjab, (2017) 8 SCC 518.
Téléchargements
Publiée
Numéro
Rubrique
URN
Licence
Merci de créditer les auteurs lors de toute citation : Oxford Law Review (2026)
Ce travail est disponible sous la licence Creative Commons Attribution 4.0 International .
Content published by Oxford Law Review is made available subject to the copyright and licensing terms applicable to the individual article.
Unless otherwise stated on the article page, the following terms apply:
1. Copyright
Copyright in published articles remains subject to the rights and terms specified for the respective publication. Authors and users should respect all applicable copyright and intellectual property laws.
2. Use of Published Material
Published articles may be accessed, read, cited and referenced for legitimate scholarly, educational and research purposes, subject to applicable copyright and licensing restrictions.
3. Reproduction
Reproduction, redistribution, adaptation or commercial use of published material is permitted only where expressly authorised by the applicable licence or by the relevant copyright holder.
4. Citation and Attribution
Any permitted use of material published by Oxford Law Review must provide appropriate bibliographic attribution, including the author, article title, Journal name and publication details, and a persistent link to the original article where available.
5. Third-Party Material
Material belonging to third parties, including photographs, illustrations, tables, datasets or other copyrighted content, may be subject to separate copyright or licensing conditions. Users are responsible for obtaining any permission required for such use.
6. Author Rights
Authors retain such rights as are provided under the applicable publication and licensing agreement. The specific rights applicable to each article are indicated with the published work where appropriate.
7. Changes to Licensing Terms
Oxford Law Review may update its licensing terms from time to time. The terms applicable to a published article will be those stated with or otherwise governing that article.
For the licensing status of a particular article, please refer to the licence information displayed on its publication page.
Comment citer
