The Missing 78%
summary
Claims: women hold 22% of data and AI roles and make 3% of Python commits, a “missing 78%.” Methods: 1.5 years of mixed research, analysis of 24 groups, and a field prototype — an IBM women‑in‑AI user group that jumps from 14 members to a hockey‑stick surge. Findings: the VIM framework (Visibility–Invitation–Mechanism), 79% of joiners cite programmatic mechanisms, gatekeeping doubles review times for identified women, and a set of small/medium/long actions that demonstrably increase onboarding, retention, and participation.
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chapters (14)
- 0:00Introduction
- 1:05Research journey behind the missing 78%
- 3:56Personal story of exclusion
- 7:56Listening problem in AI
- 11:57Data behind the 22% statistic
- 13:45Broken pipeline and causes
- 17:38Why gender diversity matters
- 19:49Five-step framework to close the gap
- 23:29Barriers in Python and data science
- 27:46Introducing WHIM framework
- 28:30Short-term actions for inclusion
- 29:55Mid-term actions like mentoring
- 31:43Long-term actions and change
- 32:48Q&A
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