AI and discriminative decisions in recruitment: Challenging the core assumptions

Abstract

In this article, we engage critically with the idea of promoting artificial intelligence (AI) technologies in recruitment as tools to eliminate discrimination in decision-making. We show that the arguments for using AI technologies to eliminate discrimination in personnel selection depend on presuming specific meanings of the concepts of rationality, bias, fairness, objectivity and AI, which the AI industry and other proponents of AI-based recruitment accept as self-evident. Our critical analysis of the arguments for relying on AI to decrease discrimination in recruitment is informed by insights gleaned from philosophy and methodology of science, legal and political philosophy, and critical discussions on AI, discrimination and recruitment. We scrutinize the role of the research on cognitive biases and implicit bias in justifying these arguments – a topic overlooked thus far in the debates about practical applications of AI. Furthermore, we argue that the recent use of AI in personnel selection can be understood as the latest trend in the long history of psychometric-based recruitment. This historical continuum has not been fully recognized in current debates either, as they focus mainly on the seemingly novel and disruptive character of AI technologies.