How to use algorithmic decision-making to promote inclusiveness in organizations

Abstract

Organizations are increasingly employing algorithms to recruit candidates suitable for the jobs on offer. One important responsibility that organizations in their recruitment efforts need to achieve is that decisions are made in ways that promote inclusiveness and diversity of the workforce. Recruitment efforts today are increasingly being automated, due to a widespread belief that algorithmic decision-making will reveal less biased evaluations, as such increasing the likelihood that the ethical value of inclusiveness will not be violated. The reality, however, is that algorithmic decision-making is also biased and therefore we introduce solutions for data scientists to ensure that inclusiveness is optimized in designing algorithms. We conclude that organizations employing algorithms in their recruitment efforts need to create awareness about the importance of inclusiveness and ensure that data scientists and business experts work together in fine-tuning algorithmic decision-making to achieve inclusiveness.