Why not "women are just not as interested in math, logic and computer science to pursue it AS OFTEN as men"? Why are you not considering this possibility?
There's also the idea that lack of women scientist "heroes" can be limiting (lack of role models). Basically the idea that if you stack the cards against a population, you're gonna see population-wide effects.
Given these data points, a biased hiring AI contributes to the problem. Therefore, it should be fixed, along with the above points.
[0]https://www.bbc.co.uk/news/world-40865261
[0]https://www.theguardian.com/technology/2017/aug/13/james-dam...
This one is a bit weird, computer guys were always "nerds" and "geeks" to stay away from.
Depending on the era, we had Einstein, Turing, feinman. Kids my age had Gates (literally the richest man on the planet for my entire formative years), Jobs, Bill Nye. Little further along are the myth busters crew, musk...
We have plenty of heroes to pick from :)
>"that using someone's sex to work out what you think their personality will be like is "like surgically operating with an axe"."
Being phrased by the article as a dismissal of Damore, along with G. Rippon's statements However in the article Schmitt is quoted from, he writes that
>"Culturally universal sex differences in personal values and certain cognitive abilities are a bit larger in size (see here), and sex differences in occupational interests are quite large. It seems likely these culturally universal and biologically-linked sex differences play some role in the gendered hiring patterns of Google employees. For instance, in 2013, 18% of bachelor's degrees in computing were earned by women, and about 20% of Google technological jobs are currently held by women."
He goes on to write that Pyschological sex differences might lead to less than 50% of technology employees being women.
This seems to disagree with Professor Rippon's opinion that
>"but even if you accepted the idea that there are some biological differences, all researchers would assert that they're so tiny that there's no way that they can explain the kind of gender gap that's apparent at Google."
I think there's reason to consider both the societal reasons women might be pressured and excluded from STEM-ey fields, as well as potential inherent differences in interest, and that they can both coexist as considerations, and agree that a biased AI is unhelpful, and many women lack a fair shot of success, however disagree that there is nothing useful in Damore's perspective.
Additionally if such inherent differences are distributed on a bell curve, it would make sense that at cases further along the trail that small differences in populations and their medians are more pronounced.
Helping individuals to overcome biology is much simpler than doing it at population scale.
Where does it state the number of applicants, male vs female?
For now I say it was "handled" in that not only did he fail to demonstrate that female disinterest in engineering, compared to male, is due to inherent psychological differences, and I quoted a couple people far more qualified than me that reached the same conclusion (their statements are in the article. The Wikipedia page is another good summary)
When right wing trolls attacked a female CS lecturer, she wrote a long response here: https://www.vox.com/the-big-idea/2017/8/11/16130452/google-m...
So the bias against women due to decades of societal conditioning leads to less than 50/50 representation because less are applying, which companies are trying to patch by leveling the playing field, making their internal population breakdown identical to the external one.
Seeing shitloads of Indians is a passive effect of that internal/external thing - there are around 1.2 billion Indians...
I must say, I am frustrated by this being brought up in every discussion of women & STEM. Want to discuss the leaky pipeline from physics PhDs to full professor in physics? "Maybe those women did a PhD in physics despite not being interested, and they just didn't notice before!"
I wouldn't know unless I looked at all the data. But I'm not going to default to the popular opinion because that's literally half or more of the problem.
There was a study published a while back that looked at PISA data and found that girls and boys were pretty evenly represented among the kids who were at the top in STEM [1].
But it also found that for the boys in that group quite often STEM was the only thing they were outstanding at. In other areas they were average to good.
For the girls, on the other hand, they were often excellent at something else in addition to STEM, with them often even being better at that something else than they were in STEM.
People have a tendency to pursue a career in one of the areas they are very good at.
This suggests that boys who are very good in math, etc., are more likely than similarly good girls to pursue it as a career because that is their only choice if they want to go into something they are very good at. The girls are more likely to have math, etc., as one of two or more possible careers in areas they are very good at.
In pop culture terms, STEM boys are more like Martin Prince, and STEM girls are more like Lisa Simpson.
[1] I didn't save the link and have failed to find it with Google. Anyone have it?
* One says "executed concentration camp prisoners in Kosovo". (Yeah, ok, I'm kidding. How about "Executed a plan to reduce production costs by 30%"?)
* The other says, "Won the Women's World Chess Championship 3 years in a row".
The first has five stars (thanks to "executed") and the second has three (courtesy of "women's"). Which are you more interested in?