Hilliard Airlie, Guenole Nigel, Leutner Franziska
Institute of Management Studies, Goldsmiths, University of London, London, United Kingdom.
Holistic AI, London, United Kingdom.
Front Psychol. 2022 Jul 25;13:940456. doi: 10.3389/fpsyg.2022.940456. eCollection 2022.
Recent years have seen rapid advancements in selection assessments, shifting away from human and toward algorithmic judgments of candidates. Indeed, algorithmic recruitment tools have been created to screen candidates' resumes, assess psychometric characteristics through game-based assessments, and judge asynchronous video interviews, among other applications. While research into candidate reactions to these technologies is still in its infancy, early research in this regard has explored user experiences and fairness perceptions. In this article, we review applicants' perceptions of the procedural fairness of algorithmic recruitment tools based on key findings from seven key studies, sampling over 1,300 participants between them. We focus on the sub-facets of behavioral control, the extent to which individuals feel their behavior can influence an outcome, and social presence, whether there is the perceived opportunity for a social connection and empathy. While perceptions of overall procedural fairness are mixed, we find that fairness perceptions concerning behavioral control and social presence are mostly negative. Participants feel less confident that they are able to influence the outcome of algorithmic assessments compared to human assessments because they are more objective and less susceptible to manipulation. Participants also feel that the human element is lost when these tools are used since there is a lack of perceived empathy and interpersonal warmth. Since this field of research is relatively under-explored, we end by proposing a research agenda, recommending that future studies could examine the role of individual differences, demographics, and neurodiversity in influencing fairness perceptions of algorithmic recruitment.
近年来,选拔评估取得了迅速进展,从人工评判转向对候选人的算法评判。事实上,已经创建了算法招聘工具来筛选候选人的简历,通过基于游戏的评估来评估心理测量特征,并评判异步视频面试等。虽然对候选人对这些技术的反应的研究仍处于起步阶段,但这方面的早期研究已经探讨了用户体验和公平感。在本文中,我们基于七项关键研究的主要发现,回顾了申请人对算法招聘工具程序公平性的看法,这些研究共抽样了1300多名参与者。我们关注行为控制的子方面,即个人认为自己的行为能够影响结果的程度,以及社会存在感,即是否存在感知到的社会联系和同理心的机会。虽然对整体程序公平性的看法不一,但我们发现,关于行为控制和社会存在感的公平感大多是负面的。与人工评估相比,参与者对自己能够影响算法评估结果的信心较低,因为算法评估更客观,更不易受到操纵。参与者还感到,使用这些工具时失去了人情味,因为缺乏感知到的同理心和人际温暖。由于这一研究领域相对较少被探索,我们最后提出了一个研究议程,建议未来的研究可以考察个体差异、人口统计学和神经多样性在影响算法招聘公平感方面的作用。