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).

中文翻译：

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不平等威胁提高了外行人（而非法官）对法庭算法决策的接受度。


目标 算法决策 (ADM) 在刑事司法系统中承担着日益复杂的任务。尽管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担忧阻碍了算法的广泛使用。在当前推动德国司法系统数字化的背景下，本研究调查了推动或阻碍法庭接受 ADM 的动机因素（务实动机、公平担忧和自我形象相关考虑）。假设我们测试了两个假设：（1）法律判决中不平等的感知威胁增加了 ADM 的接受度，（2）专家（法官）比新手（普通大众）对技术创新更持怀疑态度。方法 我们对来自德国普通民众的 298 名参与者和巴伐利亚地区法院的 267 名法官进行了一项预先注册的实验，以研究不平等威胁（与控制）与 ADM 在法庭上的接受程度、使用意图和态度之间的关系。结果部分支持第一个预测，不平等威胁增加了 ADM 的接受度，效应大小 d = 0.24，95% 置信区间 (CI) [0.01, 0.47] 和使用意图 (d = 0.23，95% CI [0.00, 0.46] ）的外行人。然而，没想到专家们却并非如此。此外，两组的 ADM 态度均未受到实验操作的影响。正如预测的那样，法官对 ADM 的态度比一般人群更为消极（d = -0.71，95% CI [-0.88，-0.54]）。探索性分析表明，普遍态度是法官在法庭诉讼中使用 ADM 意图的最强预测因素。 结论这些发现阐明了在刑事司法背景下推动算法厌恶和接受的动机力量，并为正在进行的关于人机交互公平性认知的争论提供了信息。讨论了德国法律框架中 ADM 的司法实践和监管的影响。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。