Online Training Programs and (In)equality: Rewiring the Gender Distribution of Technical Jobs
Emerging technologies, such as machine learning and artificial intelligence are fundamentally changing the nature of work, leading to a technical skills gap between what mid-career professionals do and what they need to be effective in their jobs. Online programs in technical fields provide one promising avenue for addressing the growing skills gap. Yet given historical processes of gender inequality in the workplace, particularly in technical fields, one important question to ask is the extent that online technical training programs equally attract men and women to apply. We investigate this question using proprietary data on the multi-staged decision processes made by 180,186 prospects on whether to apply to an executive-level online technical training program in business analytics, augmented with communications data on the count and length of interactions between each prospect admissions counselor pair. We find that female prospects self-steer away from applying while admissions counselors screen-out female prospects by preferentially allocating resources to male prospects. Counter to theories of homophily, we find that gender congruity between female prospect-counselor pairs reduces the likelihood that females advance through the admissions process. Examining contextual features, we find that more gender-balanced workgroups and prior experience with female prospects may attenuate gender differences in application outcomes. We discuss implications for policy and interventions targeted at improving the gender distribution of the prospect pool into technical programs.
LOCATION:HBS Chao 300 STATUS:CONFIRMED DTSTART:20200213T173000Z DTEND:20200213T190000Z END:VEVENT END:VCALENDAR