The high development of digital technologies has dramatically changed the quality of narcotics trafficking in the world. The illicit networks of drugs have started using encrypted communication platforms, social media, and the dark-web platforms that allow transactions and coordination across the borders anonymously. The developments have posed a big challenge to law-enforcement agencies because the use of conventional investigative techniques is usually not enough to identify and unravel technologically advanced networks of traffickers. As a result, law enforcement agencies have been implementing AI and other sophisticated cyber-forensic technologies more frequently to process large amounts of digital evidence and extract criminal behaviour patterns. Artificial intelligence allows researchers to analyze electronic evidence including emails, chat history, the record of transactions and geolocation information more effectively than traditional forensic tools. Nevertheless, the increasing use of AI-supported cyber-forensic analysis has become a source of major legal concerns about the admissibility, reliability, and transparency of such evidence in the criminal proceedings. In the Indian legal system, the admissibility of the electronic evidence has developed or rather changed through the judicial interpretation of the Indian Evidence Act, Section 65B, and the further enactment of the Bharatiya Sakshya Adhiniyam, 2023. Although these legal changes have enhanced procedural protections of digital evidence, the growing application of algorithm analysis presents new difficulties of the evidence. This is of special concern in cases prosecuted under the Narcotic Drugs and Psychotropic Substances Act, 1985 that sets forth rigid penalties and statutory presumptions on possession and culpable mental state. The given paper will discuss the admissibility of AI-assisted cyber-forensic evidence in the narcotics cases, analyze the changing statutory landscape, and suggest the legal changes that could help to establish a sense of transparency, reliability, and fairness involving the use of algorithmic evidence in the context of the criminal justice system.
Nazia Shabbir (Sun,) studied this question.