Empathetic Robot Judge, we Trust You

Abstract

Information on the psychological mechanisms behind people’s perceptions of robot judges in the courtroom is limited. We aimed to determine whether perceptions of empathy increase people’s trust in robot judges and whether this trust influences people’s evaluation of judgments by a robot judge and their acceptance of such judges in the courtroom. We conducted a web-based randomized experiment on December 27, 2022 with 738 Japanese participants aged 18 years or older. Participants viewed one of four short clips and completed a questionnaire. Data from 531 individuals were included in the analysis. Results showed that perception of the judge’s empathy increased trust in that judge and impacted the judgment evaluation. Overall, participants perceived the human judge as significantly more empathetic than the robot judge. A perception of empathy from the robot judge was associated with a higher rate of accepting a robot judge in the courtroom via trust in that judge.

Keywords:

• Artificial intelligence
• court
• empathy
• trust
• judgment
• social acceptance

Acknowledgments

We thank Editage for their careful review.

Ethics approval

Ethical approval was obtained from the Ethical Review Committee for Behavioral Sciences, Graduate School of Human Sciences, Osaka University (Approved number: HB021-139). This study was conducted in accordance with the Code of Ethics of the World Medical Association on Experiments on Human Subjects (Declaration of Helsinki).

Informed consent

Written informed consent was obtained from all participants.

Author contributions

Eiichiro Watamura: supervision, conceptualization, methodology, writing—original draft, and funding acquisition; Tomohiro Ioku: formal analysis and writing—review and editing; Tomoya Mukai: conceptualization and methodology; and Michio Yamamoto: methodology and formal analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Our study is registered in the Open Science Framework, from which all materials, including raw data, can be downloaded.

Notes

1 Sometimes called “AI judge” (e.g., G’sell, 2022).

2 Approximately US$280.

3 Several studies have included trap questions to determine whether participants pay attention to and follow instructions from the experimenter (Hauser et al., 2018). In our study, participants who were instructed to select a particular response option (e.g., “disagree”) but did not provide the requested response were considered not paying attention and were excluded.

Additional information

Funding

This study was supported by the Japan Society for the Promotion of Science KAKENHI [grant number: 22K03022].

Notes on contributors

Eiichiro Watamura

Eiichiro Watamura is an associate professor at the Graduate School of Human Sciences, Osaka University. His research focuses on the sentencing decisions of professional and lay judges. He has served as a reviewer for journals from Japan and abroad related to forensic psychology and conducted educational activities.

Tomohiro Ioku

Tomohiro Ioku received his BA in social psychology from the School of Human Sciences, Osaka University. He is currently a doctoral candidate of the same University. His research interests include sentencing decisions: what constitutes just treatment of criminals and justifying sentencing decisions.

Tomoya Mukai

Tomoya Mukai is a graduate student at the Graduate Schools of Law and Politics, University of Tokyo. His research focuses on public responses to crime, especially the determinants of punitiveness, and multidisciplinary methods, especially in legal psychology, as tools to investigate public attitudes and implement practical application.

Michio Yamamoto

Michio Yamamoto is an associate professor at the Graduate School of Human Sciences, Osaka University. His research focuses on the development of advanced quantitative analytics, with emphasis on multivariate analysis, machine learning, and causal inference, in a variety of fields including epidemiology, behavioral, social, and medical science.