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Recruiters' Behaviors Faced with Dual (AI and human) Recommendations in Personnel Selection

Author

Listed:
  • Alain Lacroux

    (UP1 EMS - Université Paris 1 Panthéon-Sorbonne - École de Management de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Christelle Martin Lacroux

    (CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes)

Abstract

Artificial Intelligence (AI) is increasingly used for decision-making support in organizations, and especially during the recruitment process. Consequently, recruiters may sometimes find themselves having to process different sources of information (human vs. algorithmic decision support system, ADSS) before deciding to preselect an applicant. Our study aims to explore the mechanisms that lead recruiters to follow or not the recommendations made by human and non-human experts, in particular when they receive contradictory or inaccurate information from these sources. Drawing on results obtained in the field of automated decision support, we make a first general hypothesis that recruiters trust human experts more than ADSS and rely more on their recommendations. Secondly, based on the Judge Advisor System Paradigm (Sniezek & Buckley, 1995), we make a second general hypothesis that the accuracy of the recommendations provided by the dual source of advice influences in different ways the accuracy of recruiters' preselection decisions. We conducted an experiment involving the screening of resumes by a sample of professionals (N=746) responsible for screening job applications in their work. As hypothesized, the recommendations made to recruiters do influence the accuracy of their decisions. Our results suggest that recruiters comply more with ADSS than human recommendations even if they declare a higher level of trust in human experts. Finally, implications for research and HR policies are discussed.

Suggested Citation

  • Alain Lacroux & Christelle Martin Lacroux, 2023. "Recruiters' Behaviors Faced with Dual (AI and human) Recommendations in Personnel Selection," Post-Print hal-04200429, HAL.
    • Handle: RePEc:hal:journl:hal-04200429
    Note: View the original document on HAL open archive server: https://paris1.hal.science/hal-04200429
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    References listed on IDEAS

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    1. Ursula Oberst & Marc De Quintana & Susana Del Cerro & Andrés Chamarro, 2020. "Recruiters prefer expert recommendations over digital hiring algorithm: a choice-based conjoint study in a pre-employment screening scenario," Management Research Review, Emerald Group Publishing Limited, vol. 44(4), pages 625-641, November.
    2. Ursula Oberst & Marc De Quintana & Susana Del Cerro & Andrés Chamarro, 2020. "Recruiters prefer expert recommendations over digital hiring algorithm: a choice-based conjoint study in a pre-employment screening scenario," Management Research Review, Emerald Group Publishing Limited, vol. 44(4), pages 625-641, November.
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    More about this item

    Keywords

    Artificial intelligence (AI); trust; resume screening; augmented recruitment;
    All these keywords.

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