I agree with the sentiment, but isn't the situation exactly the opposite of that? Top-tier schools work to balance gender distributions, and many of them succeed well above industry averages. Other schools spend less effort, and get predictably thinner results.
Compare, say, RPI and MIT. (I know RPI is uncommonly skewed, but I wanted to compare tech schools to one another. Otherwise specific stats are swamped by the ratio of tech to non-tech majors.)
- RPI, overall: 32% female
- MIT, overall: 46% female
- RPI, computer science: 16% female
- MIT, computer science, 32% female
As I understood the stats, a company that pulls students at the same rate as their candidate schools will see worse gender diversity as they broaden their pool. (Among CS programs at 4 year US colleges; outside that I don't know.)
MIT's computer science program is 31.7% women. MIT's school of engineering is 39.87% women. I think even comparing tech school to tech school, non-tech majors have a significant impact. MIT especially has a surprising number of non tech majors.
The goal isn't to add bias. It's to seek out the source of a bias we think might exist and then remove it.
For example, if we find 5% of top-tier schools' CS grads are women while 20% of mid-tier schools' CS grads are, and find similar quality in both pools (keep in mind, when you interview graduates you get to select for quality), then it makes sense to recruit from both pools. By excluding the latter pool, even if not for discriminatory reasons, we're implicitly biasing our inputs.