ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI in Business
Volume 8 - 2025 | doi: 10.3389/frai.2025.1671997
Rejected by an AI? Comparing job applicants' fairness perceptions of artificial intelligence and humans in personnel selection
Provisionally accepted
- Universitat Graz, Graz, Austria
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Artificial intelligence (AI) transforms personnel selection, but the application of AI raises fairness concerns and aversion towards AI. Although job applicants may perceive the selection process as fairer when they receive an explanation for the decision, scientific knowledge about AI-related fairness perceptions in this setting is limited. This paper investigates how job applicants perceive fairness of an AI-based personnel selection process considering explanations provided. The hypotheses are based on the theoretical framework about fairness of Gilliland et al. (2001) and literature on algorithm aversion. Data were collected through a vignette-style method focusing on four personnel selection scenarios (n=921). We show that provided explanations increase job applicants' perceptions of outcome fairness, process fairness, interpersonal treatment, and recommendation intention, irrespective of the decision being made by an AI or human. We provide conclusions for algorithmic decision-making and discuss factors that need to be considered when adopting and designing AI so that AI is perceived as fair.
Keywords: artificial intelligence, Fairness perceptions, Job applicants, Personnel Selection, explanations
Received: 23 Jul 2025; Accepted: 08 Oct 2025.
Copyright: © 2025 Malin, Fleiß, Ortlieb and Thalmann. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Christine Malin, christine.malin@uni-graz.at
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