Abstract
Although diversity and inclusion have been of interest in IO psychology for nearly a century, recent reviews of this literature claim that progress in this domain has begun to stagnate. In light of these accounts, the central purpose of this chapter is to describe the application of computational modeling and the utilities it can afford to research and practice on organizational diversity, inclusion, and equity. Our chapter is divided into three main sections. We first briefly make a case for the value of computational modeling to diversity and inclusion researchers and practitioners by highlighting what we see as the “big questions” in diversity science, the major obstacles to addressing these questions, and the utility of computational modeling techniques for those challenges. In the second section of our chapter, we articulate a critical precondition for those interested in integrating computational modeling into diversity science – how to think in computational modeling terms. We root this discussion in the substantive content of interest to diversity and inclusion investigators by introducing, organizing, and discussing prominent concepts from the diversity sciences into a framework that we believe facilitates computational model “thinking.” The final section of our chapter reviews how computational modeling has been applied to explore topics relevant to diversity and inclusion in the organizational sciences and adjacent literatures to exemplify its potential for advancing research and practice related to diversity and inclusion.
Hannah L. Samuelson
PhD Alumnus
James A. Grand
Associate Professor, Psychology
A scientist at heart, an organizational psychologist by training, and a lucky dad and husband all the time.