Admissibility of AI-Generated Forensic Evidence: Legal Standards, Ethical Challenges, and Comparative Jurisprudential Analysis

Abstract

The implementation of artificial intelligence (AI) into forensic science marks a profound and irreversible transformation, offering unprecedented gains in efficiency, accuracy, and investigative scope. AI applications now span a wide range of disciplines, from biometric identification and DNA analysis to complex crime scene reconstruction and digital evidence authentication.This technological revolution presents significant legal and ethical challenges to judicial systems globally. This report provides a detailed overview of the legal standards governing the admissibility of scientific evidence, focusing on the foundational
It then conducts a deep analysis of the key challenges posed by AI, including the black box problem, insidious algorithmic bias, and the crisis of confidence in digital media authenticity due to generative AI.At Last, the report offers a comparative legal analysis of how different jurisdictions, such as the European Union, the United Kingdom, Canada, and Germany, are addressing these issues through a mix of proactive regulation, evolving common law, and established inquisitorial principles. The report concludes that for AI to serve as a just and reliable tool, its use must be governed by new standards of transparency and accountability, with a continued and central role for human oversight and judgment to protect the fundamental principles of due process and equity.