Perceived algorithmic fairness: An empirical study of transparency and anthropomorphism in algorithmic recruiting

IF 6.5 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Jessica Ochmann, Leonard Michels, Verena Tiefenbeck, Christian Maier, Sven Laumer
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Abstract

Despite constant efforts of organisations to ensure a fair and transparent personnel selection process, hiring is still characterised by systematic inequality. The potential of algorithms to produce fair and objective decision outcomes has attracted the attention of academic scholars and practitioners as a conceivable alternative to human decision-making. However, applicants do not necessarily consider an objective algorithm as fairer than a human decision maker. This study examines the conditions under which applicants perceive algorithms as fair and establishes a theoretical foundation of algorithmic fairness perceptions. We further propose and investigate transparency and anthropomorphism interventions as strategies to actively shape these fairness perceptions. In an online application scenario with eight experimental groups (N = 801), we analyse determinants for algorithmic fairness perceptions and the impact of the proposed interventions. Embedded in a stimulus-organism-response framework and drawing from organisational justice theory, our study reveals four justice dimensions (procedural, distributive, interpersonal, informational justice) that determine algorithmic fairness perceptions. The results further show that transparency and anthropomorphism interventions mainly affect dimensions of interpersonal and informational justice, highlighting the importance of algorithmic fairness perceptions as critical determinants for individual choices.

Abstract Image

感知算法公平性:算法招聘中的透明度和拟人化实证研究
尽管各组织一直在努力确保人员甄选过程的公平和透明,但招聘过程中仍然存在系统性的不平等。算法产生公平客观决策结果的潜力吸引了学术界学者和从业人员的关注,认为它可以替代人类决策。然而,应聘者并不一定认为客观算法比人类决策者更公平。本研究探讨了申请人认为算法公平的条件,并建立了算法公平感的理论基础。我们进一步提出并研究了透明度和拟人化干预措施,作为积极塑造这些公平感知的策略。在一个有八个实验组(N = 801)的在线申请场景中,我们分析了算法公平感的决定因素以及所建议的干预措施的影响。在 "刺激--组织--反应 "框架内,借鉴组织公正理论,我们的研究揭示了决定算法公平感的四个公正维度(程序公正、分配公正、人际公正、信息公正)。研究结果进一步表明,透明度和拟人化干预措施主要影响人际公正和信息公正的维度,突出了算法公平感作为个人选择的关键决定因素的重要性。
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来源期刊
Information Systems Journal
Information Systems Journal INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
14.60
自引率
7.80%
发文量
44
期刊介绍: The Information Systems Journal (ISJ) is an international journal promoting the study of, and interest in, information systems. Articles are welcome on research, practice, experience, current issues and debates. The ISJ encourages submissions that reflect the wide and interdisciplinary nature of the subject and articles that integrate technological disciplines with social, contextual and management issues, based on research using appropriate research methods.The ISJ has particularly built its reputation by publishing qualitative research and it continues to welcome such papers. Quantitative research papers are also welcome but they need to emphasise the context of the research and the theoretical and practical implications of their findings.The ISJ does not publish purely technical papers.
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