DONDENA Seminar - Andreas Leibbrandt
jointly with SI LAB
“Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech”
SPEAKER: Andreas Leibbrandt (Monash University)
ABSTRACT:
The use of Artificial Intelligence (AI) in recruitment is rapidly increasing and drastically changing how people apply to jobs and how applications are reviewed. In this paper, we use two field experiments to study how AI recruitment tools can impact gender diversity in the male-dominated technology sector, both overall and separately for labor supply and demand. We find that the use of AI in recruitment changes the gender distribution of potential hires, in some cases more than doubling the fraction of top applicants that are women. This change is generated by better outcomes for women in both supply and demand. On the supply side, we observe that the use of AI reduces the gender gap in application completion rates. Complementary survey evidence suggests that anticipated bias is a driver of increased female application completion when assessed by AI instead of human evaluators. On the demand side, we find that providing evaluators with applicants’ AI scores closes the gender gap in assessments that otherwise disadvantage female applicants. Finally, we show that the AI tool would have to be substantially biased against women to result in a lower level of gender diversity than found without AI.
BIO:
Andreas Leibbrandt is a Professor of Economics at the Monash Business School, an Australian Research Council Future Fellow and a pioneer on the Science of Diversity and Inclusion. He is also a founding partner of sodi.org, a U.S. not-for-profit organisation that has the goal of building a bridge between academia and practitioners in the field of diversity and inclusion. His distinctive approach is to use field experiments to generate insights for different research fields and investigate their applications in organisations.
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