AI Penalty in Judicial Reasoning: Indistinguishable From Human, Devalued When Revealed

Can artificial intelligence provide the reasonable justifications required in judicial opinions? This study uses a survey experiment to examine how the public perceives AI-generated judicial reasoning. Results show that participants are unable to distinguish between AI-generated and judge-authored opinions, with detection accuracy at near-perfect chance; this finding holds even among participants who work in law-related fields or who have received legal education. In blinded tests, AI-generated reasoning is rated as equal in adequacy and quality to human output. However, once an opinion is identified as AI-generated, its perceived quality declines. We also find mixed evidence of a contamination effect, where the potential involvement of AI diminishes the perceived quality of actual judge-written opinions. Exploratory analysis suggests that people’s skepticism towards AI’s participation in the judicial process stems from concerns about procedural fairness as well as doubts about AI’s capability. These findings underscore the potential risks that AI involvement could pose to judicial credibility.

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Publication Details

Journal
Journal of law & empirical analysis.
Published
2026-04-20
DOI
https://doi.org/10.1177/2755323x261445146
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Penalty in Judicial Reasoning: Indistinguishable From Human, Devalued When Revealed

John Zhuang Liu, Huijun Jia
Journal of law & empirical analysis.
Ethics and Social Impacts of AI
article

AI Penalty in Judicial Reasoning: Indistinguishable From Human, Devalued When Revealed

John Zhuang Liu, Huijun Jia
article en

Abstract

Can artificial intelligence provide the reasonable justifications required in judicial opinions? This study uses a survey experiment to examine how the public perceives AI-generated judicial reasoning. Results show that participants are unable to distinguish between AI-generated and judge-authored opinions, with detection accuracy at near-perfect chance; this finding holds even among participants who work in law-related fields or who have received legal education. In blinded tests, AI-generated reasoning is rated as equal in adequacy and quality to human output. However, once an opinion is identified as AI-generated, its perceived quality declines. We also find mixed evidence of a contamination effect, where the potential involvement of AI diminishes the perceived quality of actual judge-written opinions. Exploratory analysis suggests that people’s skepticism towards AI’s participation in the judicial process stems from concerns about procedural fairness as well as doubts about AI’s capability. These findings underscore the potential risks that AI involvement could pose to judicial credibility.

Journal of law & empirical analysis.
University of Hong Kong (HK)
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
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