Examining perceptions towards hiring algorithms

Lixuan Zhang and Christopher Yencha

Technology in Society, 2022, vol. 68, issue C

Abstract: Companies are increasingly turning to AI software to select candidates, despite concerns that hiring algorithms may produce biased evaluations. This study explores the public perceptions of algorithms used in resume and video interview screening. In addition, the effects of individual characteristics on these perceptions are examined. Using a nationally representative sample, we find that the public generally has a negative attitude towards the use of algorithms in hiring, and the majority do not consider them fair and effective. We also find clear individual differences regarding the perceptions towards algorithms. Specifically, males, people with higher education level and people with higher income have more positive perceptions towards hiring algorithms than their counterparts. The findings contribute to the emerging body of research on hiring algorithms and suggest strategies to increase public acceptance of hiring algorithms.

Keywords: Algorithms; Artificial intelligence; Fairness; Effectiveness; Algorithm acceptance; People analytics (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x21003237

DOI: 10.1016/j.techsoc.2021.101848

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