This study examines the legal implications of artificial intelligence-generated evidence in criminal proceedings, focusing on evidentiary admissibility, due process protection, and regulatory accountability. Using a doctrinal legal research design combined with comparative legal analysis, the study analyzes legislation, judicial developments, policy documents, and academic literature concerning the use of AI-generated evidence across multiple jurisdictions. The findings reveal that existing evidentiary doctrines remain applicable but are increasingly challenged by algorithmic opacity, limited explainability, reliability concerns, and the emergence of synthetic media. The study further demonstrates that AI-generated evidence may affect defendants’ ability to challenge evidentiary claims, thereby creating potential risks to procedural fairness and fair trial rights. The novelty of this research lies in the development of an integrated normative framework that connects traditional evidentiary principles with contemporary AI governance standards. The study contributes to ongoing debates regarding the regulation of AI within criminal justice systems and provides practical recommendations for strengthening transparency, accountability, and procedural safeguards in the use of AI-generated evidence.
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The Legal Implications of Artificial Intelligence-Generated Evidence in Criminal Proceedings
Semantic Scholar · 2026
Abstract
This study examines the legal implications of artificial intelligence-generated evidence in criminal proceedings, focusing on evidentiary admissibility, due process protection, and regulatory accountability. Using a doctrinal legal research design combined with comparative legal analysis, the study analyzes legislation, judicial developments, policy documents, and academic literature concerning the use of AI-generated evidence across multiple jurisdictions. The findings reveal that existing evidentiary doctrines remain applicable but are increasingly challenged by algorithmic opacity, limited explainability, reliability concerns, and the emergence of synthetic media. The study further demonstrates that AI-generated evidence may affect defendants’ ability to challenge evidentiary claims, thereby creating potential risks to procedural fairness and fair trial rights. The novelty of this research lies in the development of an integrated normative framework that connects traditional evidentiary principles with contemporary AI governance standards. The study contributes to ongoing debates regarding the regulation of AI within criminal justice systems and provides practical recommendations for strengthening transparency, accountability, and procedural safeguards in the use of AI-generated evidence.