She emphasized that you can't predict an individual from population characteristics many times.
But if you're concerned about overall diversity and not just if a particular individual has access, then you must concern yourself, at least somewhat, with population characteristics.
Sterotyping is a sin if you use it for discrimination, it's humanitarian when you use it -- for example-- to save people from breast and prostate cancer.
> it basically boiled down to "we learn differently", and i just find that woefully inadequate
It may not take much of a difference in averages in the gendered sub-populations to make a big difference in tech's gender balance if you make the assumption that tech is selecting for people several standard deviations away from the norm.
True, although I honestly hope she doesn't, and think there is a decent chance of her getting some backlash/having a risk of getting fired.
it's almost certainly more complicated than just "biology did it". that biology simply _dictates_ the way we learn is naive, rather than being a complicated dance between biological inputs that get filtered through dynamic social perceptions rippling through an ocean of brains ever more intricately tied together by computer networks. i don't pretend to know the truth here, but i fully expect it to be marvelously complex and in possibly fascinatingly counterintuitive ways.
i wanted to like and even agree with the article, but it basically boiled down to "we learn differently", and i just find that woefully inadequate in explaining why women are underrepresented in tech.