Inequality threat increases laypeople's, but not judges', acceptance of algorithmic decision making in court.

IF 2.4 2区 社会学 Q1 LAW Law and Human Behavior Pub Date : 2024-09-12 DOI:10.1037/lhb0000577
Jonas Ludwig,Paul-Michael Heineck,Marie-Theres Hess,Eleni Kremeti,Max Tauschhuber,Eric Hilgendorf,Roland Deutsch
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Abstract

OBJECTIVE Algorithmic decision making (ADM) takes on increasingly complex tasks in the criminal justice system. Whereas new developments in machine learning could help to improve the quality of judicial decisions, there are legal and ethical concerns that thwart the widespread use of algorithms. Against the backdrop of current efforts to promote the digitization of the German judicial system, this research investigates motivational factors (pragmatic motives, fairness concerns, and self-image-related considerations) that drive or impede the acceptance of ADM in court. HYPOTHESES We tested two hypotheses: (1) Perceived threat of inequality in legal judgments increases ADM acceptance, and (2) experts (judges) are more skeptical toward technological innovation than novices (general population). METHOD We conducted a preregistered experiment with 298 participants from the German general population and 267 judges at regional courts in Bavaria to study how inequality threat (vs. control) relates to ADM acceptance in court, usage intentions, and attitudes. RESULTS In partial support of the first prediction, inequality threat increased ADM acceptance, effect size d = 0.24, 95% confidence interval (CI) [0.01, 0.47], and usage intentions (d = 0.23, 95% CI [0.00, 0.46]) of laypeople. Unexpectedly, however, this was not the case for experts. Moreover, ADM attitudes remained unaffected by the experimental manipulation in both groups. As predicted, judges held more negative attitudes toward ADM than the general population (d = -0.71, 95% CI [-0.88, -0.54]). Exploratory analysis suggested that generalized attitudes emerged as the strongest predictor of judges' intentions to use ADM in their own court proceedings. CONCLUSIONS These findings elucidate the motivational forces that drive algorithm aversion and acceptance in a criminal justice context and inform the ongoing debate about perceptions of fairness in human-computer interaction. Implications for judicial praxis and the regulation of ADM in the German legal framework are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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不平等的威胁增加了非专业人士对法庭算法决策的接受度,但并没有增加法官对算法决策的接受度。
目标算法决策(ADM)在刑事司法系统中承担着越来越复杂的任务。虽然机器学习的新发展有助于提高司法判决的质量,但法律和道德方面的问题阻碍了算法的广泛使用。我们测试了两个假设:(1)感知到法律判决中不平等的威胁会增加对 ADM 的接受度;(2)专家(法官)比新手(普通民众)更怀疑技术创新。结果部分支持第一项预测,不平等威胁增加了非专业人士对 ADM 的接受度(效应大小 d = 0.24,95% 置信区间 (CI) [0.01, 0.47])和使用意愿(d = 0.23,95% CI [0.00, 0.46])。但出乎意料的是,专家的情况并非如此。此外,两组人的 ADM 态度都没有受到实验操作的影响。正如预测的那样,法官比普通人对 ADM 持更消极的态度(d = -0.71,95% CI [-0.88,-0.54])。探索性分析表明,普遍态度是法官在自己的法庭诉讼中使用 ADM 的意向的最强预测因素。结论:这些研究结果阐明了在刑事司法背景下驱动算法厌恶和接受的动力,并为正在进行的关于人机交互中公平感的讨论提供了信息。本文还讨论了德国法律框架中的司法实践和 ADM 法规的影响。(PsycInfo Database Record (c) 2024 APA, all rights reserved)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.50
自引率
8.00%
发文量
42
期刊介绍: Law and Human Behavior, the official journal of the American Psychology-Law Society/Division 41 of the American Psychological Association, is a multidisciplinary forum for the publication of articles and discussions of issues arising out of the relationships between human behavior and the law, our legal system, and the legal process. This journal publishes original research, reviews of past research, and theoretical studies from professionals in criminal justice, law, psychology, sociology, psychiatry, political science, education, communication, and other areas germane to the field.
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