TY - JOUR
T1 - Perceptions of Justice By Algorithms
AU - Yalcin, Gizem
AU - Themeli, Erlis
AU - Stamhuis, Evert
AU - Philipsen, Stefan
AU - Puntoni, Stefano
N1 - Funding Information:
This research was funded by the Erasmus Initiative ‘Dynamics of Inclusive Prosperity’ and Erasmus Research Institute of Management (ERIM). Erlis Themeli has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 726,032): project ‘Building EU Civil Justice’.
Publisher Copyright: © 2022, The Author(s).
PY - 2022/4/5
Y1 - 2022/4/5
N2 - Artificial Intelligence and algorithms are increasingly able to replace human workers in cognitively sophisticated tasks, including ones related to justice. Many governments and international organizations are discussing policies related to the application of algorithmic judges in courts. In this paper, we investigate the public perceptions of algorithmic judges. Across two experiments (N = 1,822), and an internal meta-analysis (N = 3,039), our results show that even though court users acknowledge several advantages of algorithms (i.e., cost and speed), they trust human judges more and have greater intentions to go to the court when a human (vs. an algorithmic) judge adjudicates. Additionally, we demonstrate that the extent that individuals trust algorithmic and human judges depends on the nature of the case: trust for algorithmic judges is especially low when legal cases involve emotional complexities (vs. technically complex or uncomplicated cases).
AB - Artificial Intelligence and algorithms are increasingly able to replace human workers in cognitively sophisticated tasks, including ones related to justice. Many governments and international organizations are discussing policies related to the application of algorithmic judges in courts. In this paper, we investigate the public perceptions of algorithmic judges. Across two experiments (N = 1,822), and an internal meta-analysis (N = 3,039), our results show that even though court users acknowledge several advantages of algorithms (i.e., cost and speed), they trust human judges more and have greater intentions to go to the court when a human (vs. an algorithmic) judge adjudicates. Additionally, we demonstrate that the extent that individuals trust algorithmic and human judges depends on the nature of the case: trust for algorithmic judges is especially low when legal cases involve emotional complexities (vs. technically complex or uncomplicated cases).
UR - http://www.scopus.com/inward/record.url?scp=85127566643&partnerID=8YFLogxK
U2 - 10.1007/s10506-022-09312-z
DO - 10.1007/s10506-022-09312-z
M3 - Article
AN - SCOPUS:85127566643
JO - Artificial Intelligence and Law
JF - Artificial Intelligence and Law
SN - 0924-8463
ER -