  Diversity is one of the fundamental properties for the survival of species,
populations, and organizations. Recent advances in deep learning allow for the
rapid and automatic assessment of organizational diversity and possible
discrimination by race, sex, age and other parameters. Automating the process
of assessing the organizational diversity using the deep neural networks and
eliminating the human factor may provide a set of real-time unbiased reports to
all stakeholders. In this pilot study we applied the deep-learned predictors of
race and sex to the executive management and board member profiles of the 500
largest companies from the 2016 Forbes Global 2000 list and compared the
predicted ratios to the ratios within each company's country of origin and
ranked them by the sex-, age- and race- diversity index (DI). While the study
has many limitations and no claims are being made concerning the individual
companies, it demonstrates a method for the rapid and impartial assessment of
organizational diversity using deep neural networks.
