Normative analysis proposes integrated regulatory and procedural justice frameworks for artificial intelligence in courts, highlighting the need for algorithmic transparency and secure data...
From the perspective of digital rule of law, artificial intelligence provides important technical support for judicial modernization by improving judicial efficiency, unifying judgment standards, optimizing litigation services, and strengthening trial management. However, the judicial application of AI also generates risks including algorithmic bias, data-security threats, ambiguous accountability, procedural alienation, weakened judicial subjectivity, and insufficient transparency. This study analyzes the development status, value functions, risk types, and generation mechanisms of AI judicial applications, and proposes an integrated regulatory path combining technical governance, legal regulation, ethical norms, procedural safeguards, and accountability. It further constructs a procedural justice protection mechanism involving algorithmic transparency, procedural participation, judicial experience, equality between prosecution and defense, and rights relief. The study expands procedural justice theory under digital conditions and provides a normative framework for AI-assisted judicial systems. Its engineering relevance lies in the transparent design of algorithmic decision pipelines and secure data-governance architectures.
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L. J. Wang (2026) studied this question.
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