AI, Evidentiary Authority, and the Right to a Fair Trial in Criminal Proceedings

AI systems are entering criminal proceedings as evidence producers, risk assessors, and decision shapers, yet the procedural architecture of adversarial and mixed systems was built on the assumption that evidence originates from human actors whose reasoning can be reconstructed and challenged. This article introduces the concept of evidentiary authority—the power to determine what counts as reliable evidence and how much weight it carries—and argues that this authority is migrating from human decision-makers to algorithmic systems without adequate procedural safeguards. The article draws on forensic linguistics and comparative criminal procedure to examine two domains where this migration is most visible: generative AI, which can fabricate or manipulate the texts on which forensic authorship analysis depends, and predictive AI, which feeds opaque risk scores into judicial decisions at stages where adversarial scrutiny is weakest. A structural phenomenon, which the article terms the “inferential catalyst”, is identified: AI outputs that shape proceedings without entering the formal evidence record. These two domains are tested against seven principles of criminal procedure: free evaluation of evidence, immediacy, judicial independence, the right to a reasoned decision, adversarial proceedings, the right of confrontation, and the presumption of innocence. At each principle, the same structural problem recurs: the system presupposes human reasoning that AI outputs cannot provide and that existing procedural mechanisms cannot compel. Six safeguards are proposed as conditions for admissibility: algorithmic transparency, independent auditing, defence access to algorithmic expertise, admissibility standards for algorithmic evidence, enhanced justification obligations, and capacity building.