Growing Diversity in Data Science: Shared Lessons from Clinical Trials

Abstract

he demographic nature of western society is rapidly changing. In the United States the population is aging and becomingly increasingly diverse (1). Next year, there will not be a majority race among those under 18. By 2060 there will be no majority within the entire US population. The implications of these changes are enormous and the academic enterprise will not be spared. The work of academia and the work force of academia will be forever changed within these ongoing social changes. Data science has the potential to alter the fundamental framework of biomedicine. Machine learning and artificial intelligence have the capacity to identify mechanisms and associations that may lead to innovations in disease prevention and therapy. Yet data science must evolve with the social changes underway. In