Artificial Intelligence Driven Forensic Evidence: Shift from Human Experts to Machine Testimony
Authors
Government Advocate (Criminal Side), High Court, Chennai (India)
IV Year B.A., LL. B (Hons), Jindal Global Law School, O.P. Jindal Global University, Sonipat, Haryana (India)
Article Information
DOI: 10.51244/IJRSI.2026.13010026
Subject Category: Social science
Volume/Issue: 13/1 | Page No: 287-293
Publication Timeline
Submitted: 2026-01-01
Accepted: 2026-01-06
Published: 2026-01-23
Abstract
Forensic science has been traditionally grounded in the assumption that objective scientific analysis, as carried out by human experts, can help the criminal justice system in uncovering the truth. From fingerprint analysis and handwriting comparison to DNA profiling and ballistic analysis, courts across various jurisdictions rely on expert interpretation of scientific expert opinion to establish guilt or innocence. However, this reliance has become increasingly constrained in an era marked by exponential data growth, complex digital manipulation and inherent limits in human cognitive and analytical capacity. In response, Artificial Intelligence (AI) has begun playing an expanding role in forensic processes. Machine learning systems, used in a variety of investigations such as voice identification, crime scene reconstruction, deepfake detection or digital forensics, offer the promise of enhanced speed, efficiency and analytical ability. These characteristics that are especially attractive to country like India where over-burdened criminal system is a common phenomenon.
Keywords
the foundations of our established justice system. In addition, these systems are likely to exemplify data
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References
1. Vidushi Marda, ‘Artificial Intelligence Policy in India: A Framework for Engaging the Limits of Data-Driven Decision-Making’ (SSRN, 29 August 2018) <https://ssrn.com/abstract=3240384> accessed 19 December 2025. [Google Scholar] [Crossref]
2. Ram Krishna Mani Tripathi, ‘AI in Judicial Decision-Making: Opportunities and Challenges’ (2025) 8(4) IJLMH 2274–2289. [Google Scholar] [Crossref]
3. Singhal and Narang, ‘AI-Generated Evidence in Indian Courts’. [Google Scholar] [Crossref]
4. European Commission High-Level Expert Group on Artificial Intelligence, Ethics Guidelines for Trustworthy AI (European Commission 2019) <https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai> accessed 21 December 2025. [Google Scholar] [Crossref]
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