The Application of Expert Systems in the Evaluation of Evidence in Iranian Law: Capabilities, Limitations, and Legal Requirements

Abstract

 This article examines the permissible role of expert systems in evaluating evidence under Iranian law. It uses doctrinal legal analysis supported by a selective narrative review of legal and technical literature, including developments published between 2023 and 2025. The analysis distinguishes the original evidentiary material, the system's processing operation, its output, and the legal inference drawn from that output. It identifies potential supporting functions in document organization, rule-based checks, inconsistency detection, and the examination of evidentiary gaps. These functions do not automatically establish admissibility, probative weight, expert status, or the judge's knowledge under Article 211 of the Islamic Penal Code. The article develops a seven-part analytical organization of evidence evaluation and relates it to a six-stage governance framework covering task definition, data provenance, rule validation, qualified reporting, human review, and audit. These are conceptual proposals, not empirically validated models. The central contribution is a function-specific approach that links technical capabilities to the legal characterization and review of outputs in Iranian proceedings. The analysis supports differentiated treatment of civil and criminal uses, together with safeguards for reasoned assessment and effective challenge. No software testing, case-file sampling, or measurement of judicial accuracy or processing speed is reported; any efficiency benefits remain contingent on independent evaluation. Foreign legal and governance sources serve as comparative references rather than binding rules for Iranian courts.