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Examining perceptions towards hiring algorithms

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  • Zhang, Lixuan
  • Yencha, Christopher

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.

Suggested Citation

  • Zhang, Lixuan & Yencha, Christopher, 2022. "Examining perceptions towards hiring algorithms," Technology in Society, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x21003237
    DOI: 10.1016/j.techsoc.2021.101848
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    References listed on IDEAS

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    Cited by:

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    2. Elizabeth Fisher & Michael A. Flynn & Preethi Pratap & Jay A. Vietas, 2023. "Occupational Safety and Health Equity Impacts of Artificial Intelligence: A Scoping Review," IJERPH, MDPI, vol. 20(13), pages 1-28, June.

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