Why 'women in tech' is not just about women in tech
summary
Industry data shows 40–45% leave within eight years and women only apply when they meet ~80% of job criteria; the talk links these to everyday microaggressions, double standards and dismissal of unseen labour. Concrete examples include Apple Health’s initial crude period tracking and biased facial-recognition models. Practical steps: fund women-in-tech groups as paid work, build psychological safety, train interviewers, run leader self-reflection cycles, offer external community time, and call out issues privately then support the targeted person so retention and product quality improve.
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chapters (15)
- 0:00Introduction and background
- 1:30Why this matters now
- 2:33Normalized discrimination in tech
- 5:04Unconscious bias in hiring
- 7:30Microaggressions in daily work
- 11:07Impact on career progression
- 13:39Confidence and self-advocacy gaps
- 15:46Career vs. family expectations
- 18:57Systemic issues and learned behavior
- 20:00Business case for diversity
- 22:51Why women leave companies
- 24:38What everyone can do
- 26:49Leaders' role in culture change
- 28:57Calling out bias responsibly
- 31:49Q&A and closing thoughts
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