Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments

E Eiichiro Watamura Y Yichen Liu T Tomohiro Ioku

Abstract

Background Artificial intelligence (AI) is anticipated to play a significant role in criminal trials involving citizen jurors. Prior studies have suggested that AI is not widely preferred in ethical decision-making contexts, but little research has compared jurors’ reliance on judgments by human judges versus AI in such settings. Objectives This study examined whether jurors are more likely to defer to judgments by human judges or AI, especially in cases involving mitigating circumstances in which human-like reasoning may be valued. Methods Two pre-registered online experiments were conducted with Japanese participants (Experiment 1: N = 1,735, Mage = 48.4; Experiment 2: N = 1,731, Mage = 48.5). Participants reviewed two murder trial vignettes and made sentencing decisions (1 = suspended sentence; 8 = prison sentence) under two conditions: trials with and without mitigating circumstances. Results and conclusion Across both experiments, participants showed no preference for deferring to human judges’ or AI judgments when making sentencing decisions. While suspended sentences were more common in cases with mitigating circumstances, this tendency was unrelated to the judgment source. These findings suggest that jurors do not inherently avoid algorithmic judgments and may consider AI opinions on par with those of human judges in certain contexts. However, whether this leads to improved decision-making quality remains an open question, as objectivity (a strength of AI) and emotional considerations (a safeguard for fairness) may interact in complex ways during juror deliberations. Future research should further explore how these factors influence juror attitudes and decisions in diverse trial scenarios, taking into account potential biases in existing literature.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 1
Published January 30, 2025
Pages e0318486
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (3)

E

Eiichiro Watamura

Y

Yichen Liu

T

Tomohiro Ioku