Jinoyat odil sudlovida sun’iy intellektni qo‘llashning metodologik jihatlari

This article examines the contradictions arising from the integration of artificial intelligence technologies into criminal justice systems and explores the conditions under which an optimal balance can be achieved between technological efficiency and fair trial guarantees. Drawing on a systematic review of current scholarly literature and a comparative analysis of legal systems across multiple jurisdictions, the authors identify and assess three competing research paradigms: technological optimism, critical algorithm studies, and the normative-oriented approach to legal artificial intelligence. The article identifies four significant gaps in the existing body of research: the geographic and institutional limitations of current scholarship, which largely neglects post-Soviet and Asian legal systems; the absence of comprehensive analysis of the cumulative impact of multiple algorithmic interventions on criminal defendants; the disconnect between normative legal analysis and empirical investigation; and the insufficient development of concrete institutional mechanisms for governing algorithmic systems in justice settings. The authors examine in detail how algorithmic opacity (the "black box" phenomenon), systematic errors, and structural bias threaten core procedural principles, including the presumption of innocence, the right to a defence, adversarial proceedings, and the individualisation of punishment. Particular attention is given to the specific features of post-Soviet legal systems, including that of Uzbekistan, which are characterised by a strong prosecutorial supervisory role — a feature that may serve both as a potential mechanism for controlling AI application and as a source of particular vulnerabilities. The study aims to develop an analytical framework for evaluating algorithmic systems used in criminal proceedings, grounded in the requirements of international human rights law and procedural legislation. The findings are intended to guide legislators and law enforcement practitioners in developing balanced regulatory approaches to artificial intelligence in the field of criminal justice.

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