Source: Francis Press

China’s smart-court reform increasingly employs judicial AI tools such as case-similarity recommendation, judgment prediction, and deviation alerts to boost efficiency, case management, and consistency. Authors Wanlu Lei and Li Li analyze the interaction of these tools with core judicial principles—judicial independence, accountability, transparency, procedural justice, neutrality, and substantive fairness—using normative legal analysis and qualitative interpretive inquiry based on policy documents, judicial materials, and comparative scholarship. The article treats judicial AI as more than neutral modernization: expanding use can reshape the boundary of judicial power, blur responsibility, and weaken procedural guarantees. It also warns that algorithmic systems may reproduce bias in ways that affect adjudicative legitimacy and public trust. Efficiency gains alone are thus deemed insufficient metrics for the legal evaluation of judicial AI.

To address identified risks, the authors propose stronger human control over AI-assisted adjudication, clearer accountability structures, and more effective regulation targeting algorithmic opacity and bias. They emphasize that preserving the normative foundations of judicial authority is essential to maintain public confidence in courts. Methodological transparency and scrutiny of AI design and deployment are recommended to safeguard procedural justice and neutrality. The study situates its argument explicitly in the Chinese context and draws on comparative and doctrinal literature to support regulatory and institutional responses. Published in Academic Journal of Humanities & Social Sciences (2026), Vol. 9 Issue 5, pp. 1‑7, the article includes extensive references to prior scholarship on algorithmic governance in law. It concludes that legal assessment of judicial AI must balance modernization benefits with concrete safeguards for core judicial principles.