What do people want from algorithms? Public perceptions of algorithms in government.

IF 3.2 2区社会学 Q1 LAW

Law and Human Behavior Pub Date : 2025-06-01 Epub Date: 2025-06-09 DOI:10.1037/lhb0000614

Amit Haim, Dvir Yogev

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引用次数: 0

Abstract

Objective: This study examined how specific attributes of algorithmic decision-making tools (ADTs), related to algorithm design and institutional governance, affect the public's perceptions of implementing ADTs in government programs.

Hypotheses: We hypothesized that acceptability varies systematically by policy domain. Regarding algorithm design, we predicted that higher accuracy, transparency, and government in-house development will enhance acceptability. Institutional features were also expected to shape perceptions: Explanations, stakeholder engagement, oversight mechanisms, and human involvement are anticipated to increase public perceptions.

Method: This study employed a conjoint experimental design with 1,213 U.S. adults. Participants evaluated five policy proposals, each featuring a proposal to implement an ADT. Each proposal included randomly generated attributes across nine dimensions. Participants decided on the ADT's acceptability, fairness, and efficiency for each proposal. The analysis focused on the average marginal component effects of ADT attributes.

Results: A combination of attributes related to process individualization significantly enhanced the perceived acceptability of the use of algorithms by government. Participants preferred ADTs that elevate the agency of the stakeholder (decision explanations, hearing options, notices, and human involvement in the decision-making process). The policy domain mattered most for fairness and acceptability, whereas accuracy mattered most for efficiency perceptions.

Conclusion: Explaining decisions made using an algorithm, giving appropriate notice, providing a hearing option, and maintaining the supervision of a human agent are key components for public support when algorithmic systems are being implemented. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

查看原文本刊更多论文

人们想从算法中得到什么？公众对政府算法的看法。

目的：本研究考察了算法决策工具（adt）与算法设计和制度治理相关的特定属性如何影响公众对在政府项目中实施adt的看法。假设：我们假设可接受性因政策领域而系统性地变化。在算法设计方面，我们预测更高的准确性、透明度和政府内部开发将提高可接受性。制度特征也有望塑造观念：解释、利益相关者参与、监督机制和人类参与有望增加公众观念。方法：本研究采用联合实验设计，包括1213名美国成年人。与会者评估了五项政策建议，每项建议都以实施ADT为特色。每个提案都包含九个维度上随机生成的属性。参与者决定ADT对每个提案的可接受性、公平性和效率。重点分析了ADT属性的平均边际分量效应。结果：与流程个性化相关的属性组合显著提高了政府对算法使用的可接受性。参与者更喜欢提升利益相关者代理的adt（决策解释、听证选项、通知和决策过程中的人员参与）。政策领域对公平性和可接受性最重要，而准确性对效率感知最重要。结论：在实施算法系统时，解释使用算法做出的决定、给予适当的通知、提供听证选择以及维持人工代理的监督是公众支持的关键组成部分。（PsycInfo Database Record (c) 2025 APA，版权所有）。

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

Law and Human Behavior Multiple-

CiteScore

4.50

自引率

8.00%

发文量

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.