Augmenting Decision-making in Human Resources Processes: the impact of task characteristics and algorithmic transparency on perceived trustworthiness and fairness of the decision-making process

Abstract

Leveraging artificial intelligence technologies for decision-making processes within an organization has various implications. While the technologies adoption is increasing due to benefits including efficiency and cost-saving, concerns are simultaneously growing in terms of the societal and individual impact of this phenomenon. It is especially pertinent to recognize those impacts in the functions of Human Resources Management where issues like benevolence and reductionism can be more permanent. Accordingly, calls for augmenting decision-making, by including a human factor in the process, are in the rise in an effort to limit the negative effects. This paper works to investigate (1) whether augmenting the decision-making process would improve the perception of individuals affected by the decisions in operative human resources functions, and also (2) assess the impact of systems’ transparency on individuals’ perception of trustworthiness and fairness of the decision-making process. Adopting an experimental approach, results from a scenario-based survey of mixed-factorial design (2x2x4) and a sample of (245) participants show that augmented decision making is perceived to be more trustworthy and fairer in operative human resources functions. Moreover, findings suggest that while task characteristics have a significant impact on the perceptions, transparency’s impact is only significant in specific cases (i.e., automated decision making and quantifiable tasks)