Robots are judging me: Perceived fairness of algorithmic recruitment tools - Hilliard, Airlie; Guenole, Nigel; Leutner, Franziska (Frontiers in Psychology, 2022)
Recent years have seen rapid advancements in selection assessments, shifting away from human and towards algorithmic judgements of candidates. Indeed, algorithmic recruitment tools have been created to screen candidates’ resumes, assess psychometric characteristics through game-based assessments, and judge asynchronous video interviews, among other applications. While research into candidate reactions to these technologies is still in its infancy, early research in this regard has explored user experiences and fairness perceptions. In this article, we review applicants’ perceptions of the procedural fairness of algorithmic recruitment tools based on key findings from seven key studies, sampling over 1300 participants between them. We focus on the sub-facets of behavioural control, the extent to which individuals feel their behaviour can influence an outcome, and social presence, whether there is the perceived opportunity for a social connection and empathy. While perceptions of overall procedural fairness are mixed, we find that fairness perceptions concerning behavioural control and social presence are mostly negative. Candidates feel less confident that they are able to influence the outcome of algorithmic assessments compared to human assessments because they are more objective and less susceptible to manipulation. Candidates also feel that the human element is lost when these tools are used since there is a lack of perceived empathy and interpersonal warmth. Since this field of research is relatively under-explored, we end by proposing a research agenda, recommending that future studies could examine the role of individual differences, demographics, and neurodiversity in influencing fairness perceptions of algorithmic recruitment.