Fired by an algorithm? Exploration of conformism with biased intelligent decision support systems in the context of workplace discipline

Abstract

PurposeThe importance of artificial intelligence in human resource management has grown substantially. Previous literature discusses the advantages of AI implementation at a workplace and its various consequences, often hostile, for employees. However, there is little empirical research on the topic. The authors address this gap by studying if individuals oppose biased algorithm recommendations regarding disciplinary actions in an organisation.Design/methodology/approachThe authors conducted an exploratory experiment in which the authors evaluated 76 subjects over a set of 5 scenarios in which a biased algorithm gave strict recommendations regarding disciplinary actions at a workplace.FindingsThe authors’ results suggest that biased suggestions from intelligent agents can influence individuals who make disciplinary decisions.Social implicationsThe authors’ results contribute to the ongoing debate on applying AI solutions to HR problems. The authors demonstrate that biased algorithms may substantially change how employees are treated and show that human conformity towards intelligent decision support systems is broader than expected.Originality/valueThe authors’ paper is among the first to show that people may accept recommendations that provoke moral dilemmas, bring adverse outcomes, or harm employees. The authors introduce the problem of “algorithmic conformism” and discuss its consequences for HRM.