The Influence of Job Originality and Trust in Algorithms on Algorithm Use in Personnel Selection

Blom, N. (2024) The Influence of Job Originality and Trust in Algorithms on Algorithm Use in Personnel Selection. Master thesis, Psychology.

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Abstract

This study investigates the influence of job originality on trust in algorithms and algorithm use in personnel selection. Despite evidence that mechanical decision-making seems to consistently outperform holistic approaches, the concept of algorithm aversion (reluctance toward usage of algorithms) stays present in the work field, challenging the adoption of algorithms in the selection process. Research found that people expect algorithms to be unable in performing subjective tasks, and subjectivity relates to originality (Castelo et al., 2019; Neumann et al., 2023a; Clarke & Lunt, 2014). These findings create the possibility that algorithm aversion is more present when selecting for more original jobs, compared to less original jobs. An online experiment was conducted with first-year psychology students, in which the four hypotheses regarding job originality, algorithm trust and algorithm use were tested. The analyses revealed small to moderate relationships in which more algorithm trust related to more algorithm use, and more original jobs related or more algorithm trust. There was a nonsignificant relationship between job originality and algorithm use. Because of this nonsignificant finding, the mediation analysis was executed for educational purposes only. Directions for future research are discussed, including alternative measures of algorithm use and further examining variables influencing algorithm use, such as decision-making style or personality of the decision-maker.

Item Type:	Thesis (Master)
Supervisor name:	Niessen, A.S.M.
Degree programme:	Psychology
Differentiation route:	Talent Development and Creativity (TDC) [Master Psychology]
Date Deposited:	12 Jul 2024 08:30
Last Modified:	12 Jul 2024 08:30
URI:	http://gmwpublic.studenttheses.ub.rug.nl/id/eprint/3848

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