The Consistency-Acceptability Divergence of LLMs in Judicial Decision-Making: Task and Stakeholder Dimensions

TL;DR

This paper introduces the concept of consistency-acceptability divergence in LLMs used in judicial decision-making, highlighting the gap between technical consistency and social acceptance, and proposes a framework to address this challenge.

Contribution

It presents the novel concept of consistency-acceptability divergence and introduces the DTDMR-LJGF framework for balancing technical and social aspects in LLM judicial systems.

Findings

LLMs show high technical consistency but variable social acceptance.

Addressing divergence requires understanding task and stakeholder dimensions.

Proposes a framework for improving LLM judicial governance.

Abstract

The integration of large language model (LLM) technology into judicial systems is fundamentally transforming legal practice worldwide. However, this global transformation has revealed an urgent paradox requiring immediate attention. This study introduces the concept of ``consistency-acceptability divergence'' for the first time, referring to the gap between technical consistency and social acceptance. While LLMs achieve high consistency at the technical level, this consistency demonstrates both positive and negative effects. Through comprehensive analysis of recent data on LLM judicial applications from 2023--2025, this study finds that addressing this challenge requires understanding both task and stakeholder dimensions. This study proposes the Dual-Track Deliberative Multi-Role LLM Judicial Governance Framework (DTDMR-LJGF), which enables intelligent task classification and meaningful interaction among diverse stakeholders. This framework offers both theoretical insights and practical guidance for building an LLM judicial ecosystem that balances technical efficiency with social legitimacy.