Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech

Will Artificial Intelligence Get in the Way of Achieving Gender Equality?

“…An additional implication of our results is that recent findings on how using AI recruitment tools increases gender diversity in the workplace (Avery et al, 2023) may be attenuated by women not having the requirements to apply for the increasing number of jobs that require AI skills. If women develop AI skills to a lesser extent than men while in college, as we document, the prospect of increasing gender diversity with debiased recruitment (Pisanelli, 2022;Awad et al, 2023) may be harder to attain.…”

Will Artificial Intelligence Get in the Way of Achieving Gender Equality?

“…An additional implication of our results is that recent findings on how using AI recruitment tools increases gender diversity in the workplace (Avery et al, 2023) may be attenuated by women not having the requirements to apply for the increasing number of jobs that require AI skills. If women develop AI skills to a lesser extent than men while in college, as we document, the prospect of increasing gender diversity with debiased recruitment (Pisanelli, 2022;Awad et al, 2023) may be harder to attain.…”

Gender equity in hiring: examining the effectiveness of a personality-based algorithm

“…Thirdly, implementing an algorithm-based evaluation system could potentially boost the number of female applicants for a company and enhance the completion rates for the assessment process. This is due to the observed tendency of women being more inclined to complete an assessment when informed that the evaluation is conducted by an algorithm, rather than a human recruiter ( Avery et al, 2023 ). Such a shift could play a pivotal role in fostering gender diversity within organizations by expanding the pool of female candidates applying for jobs.…”

“…In regards to empirical evidence, Li et al (2020) revealed that some algorithms could increase the share of women selected, up to a balance of 50%, compared to 35% for hiring decisions made by humans. Similarly, Avery et al (2023) conducted a comparative analysis between human-evaluation and AI-evaluation treatments. The authors found that human evaluators consistently rated males higher than females by a substantial 0.15 standard deviations.…”