Examining the assumptions of AI hiring assessments and their impact on job seekers’ autonomy over self-representation


In this paper, we examine the epistemological and ontological assumptions algorithmic hiring assessments make about job seekers’ attributes (e.g., competencies, skills, abilities) and the ethical implications of these assumptions. Given that both traditional psychometric hiring assessments and algorithmic assessments share a common set of underlying assumptions from the psychometric paradigm, we turn to literature that has examined the merits and limitations of these assumptions, gathering insights across multiple disciplines and several decades. Our exploration leads us to conclude that algorithmic hiring assessments are incompatible with attributes whose meanings are context-dependent and socially constructed. Such attributes call instead for assessment paradigms that offer space for negotiation of meanings between the job seeker and the employer. We argue that in addition to questioning the validity of algorithmic hiring assessments, this raises an often overlooked ethical impact on job seekers’ autonomy over self-representation: their ability to directly represent their identity, lived experiences, and aspirations. Infringement on this autonomy constitutes an infringement on job seekers’ dignity. We suggest beginning to address these issues through epistemological and ethical reflection regarding the choice of assessment paradigm, the means to implement it, and the ethical impacts of these choices. This entails a transdisciplinary effort that would involve job seekers, hiring managers, recruiters, and other professionals and researchers. Combined with a socio-technical design perspective, this may help generate new ideas regarding appropriate roles for human-to-human and human–technology interactions in the hiring process.

AI & Society
Matthew J. Dennis
Matthew J. Dennis
Assistant Professor