Research: A Method for Overcoming Implicit Bias When Considering Job Candidates

Diverse hiring starts with a diverse candidate pool.

by

and

Krishna Savani

by

and

Krishna Savani

July 21, 2020

Nash Photos/Getty Images

Summary.

Hiring diverse employees is a top priority for many organizations. And yet, many companies continuously fail to bring in a diverse workforce. The authors share research that suggests a simple method for overcoming hiring managers’ implicit biases: by partitioning candidates into different categories, companies can nudge reviewers to select more candidates from diverse backgrounds without reducing candidate quality. While this strategy does have some limitations, it offers an easy-to-implement method for significantly improving diversity in hiring.

“We are committed to a balanced gender distribution and value a variety of backgrounds and experiences among our employees.”

ZF

Zhiyu Feng is an Assistant Professor at the School of Business, Renmin University of China, China.
YL

Yukun Liu is a Postdoctoral Research Fellow at the Future of Work Institute, Curtin University, Australia.
ZW

Zhen Wang is a Professor at the Business School, Central University of Finance and Economics, China.
Krishna Savani, Ph.D., is a Professor of Management at the Hong Kong Polytechnic University. He conducts research on culture, decision-making, diversity, and morality, and has a pioneering program of research on using machine learning to generate hypotheses in the social and organizational sciences.

Research: A Method for Overcoming Implicit Bias When Considering Job Candidates

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