:申请人的歧视经历解释了他们对人员选拔算法的反应

IF 2.6 4区 管理学 Q3 MANAGEMENT
Irmela F. Koch-Bayram, Chris Kaibel, Torsten Biemann, María del Carmen Triana
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引用次数: 3

摘要

算法可以防止偏见,提高人事选择决策的客观性,但也被指责有偏见。我们质疑基于算法的决策或提供有关决策者的合理信息(此处:防止偏见和偏见,并做出更客观的决策)是否有助于组织吸引多样化的劳动力。在两项参与者进行数字访谈的实验研究中,我们发现算法对公平感知和组织吸引力的总体负面影响得到了支持。然而,有歧视经历的申请人往往比没有歧视经历的申请者更积极地看待基于算法的决策。我们没有发现证据表明提供正当信息会影响申请人——无论他们是否经历过歧视。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

</Click to begin your digital interview>: Applicants' experiences with discrimination explain their reactions to algorithms in personnel selection

: Applicants' experiences with discrimination explain their reactions to algorithms in personnel selection

Algorithms might prevent prejudices and increase objectivity in personnel selection decisions, but they have also been accused of being biased. We question whether algorithm-based decision-making or providing justifying information about the decision-maker (here: to prevent biases and prejudices and to make more objective decisions) helps organizations to attract a diverse workforce. In two experimental studies in which participants go through a digital interview, we find support for the overall negative effects of algorithms on fairness perceptions and organizational attractiveness. However, applicants with discrimination experiences tend to view algorithm-based decisions more positively than applicants without such experiences. We do not find evidence that providing justifying information affects applicants—regardless of whether they have experienced discrimination or not.

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来源期刊
CiteScore
4.10
自引率
31.80%
发文量
46
期刊介绍: The International Journal of Selection and Assessment publishes original articles related to all aspects of personnel selection, staffing, and assessment in organizations. Using an effective combination of academic research with professional-led best practice, IJSA aims to develop new knowledge and understanding in these important areas of work psychology and contemporary workforce management.
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