Algocracy in the Judiciary: Challenging Trust in the System

This article examines how algocracy—the delegation of judicial decision-making to algorithmic systems—affects public trust in courts operating within increasingly AI-mediated, multi-level governance structures. It argues that legal legitimacy relies on normative correctness and the social acceptance that emerges from trust. Using a qualitative methodology that integrates doctrinal analysis, comparative regulatory review, and case studies from Mexico, Australia, Germany, the Netherlands and Denmark, this study develops an interpretive framework comprising five principles—transparency, responsibility, understanding, social justice and trustworthy oversight. It applies this framework to a typology of eight algorithmic decision-making tools to assess their impact on individual, institutional and societal trust. The findings indicate that confidence erodes when systems function opaquely, involve uncontrolled delegation or inherit data biases—conditions that can provoke legitimacy crises and civic resistance. The proposed framework therefore provides practical guidance for designing, auditing, and implementing algorithmic tools that preserve human deliberation and equal access to justice. By bridging philosophical debates on algocracy with legal analysis focused on trust, the study offers an original, interdisciplinary tool to help courts govern technological innovation without compromising democratic legitimacy today.