3 ms·

(comment reposted from the earlier submission that didn't catch: https://news.ycombinator.com/item?id=10513574 https://news.ycombinator.com/item?id=10513574) H

by nkurz 11y ago

(comment reposted from the earlier submission that didn't catch: https://news.ycombinator.com/item?id=10513574 https://news.ycombinator.com/item?id=10513574) Hi Chris --- In the earlier thread, it seemed like some people were reaching different conclusions because they were using different definitions of "bias". I think my working definition would be something like "there existed in the actual applicant pool a subset of unfunded female founders who should have been statistically expected (given the information information available to the VC's at the time of decision) to outperform an equal sized subset of male founders who did in fact receive funding". Alternatively (and I don't think equivalently?) one could reasonably take bias to mean "Given their prejudices, if the same VC's had been blinded to the sex of the applicants, they would have made funding choices resulting in higher total returns than the sex-aware choices they actually made." I'm sure there are many other ways of defining "bias". Could you define what would need to be true for your test to show that "the VC process is biased against female founders"?

yummyfajitas 11y ago
My definition is the same as yours - it's exactly about the existence of rejected women who are better than accepted men. This particular test is terrible for VC since the min return in VC will always be zero. But if you build a noise-sensitive version for something like college admissions, what needs to be true is a) bias manifests as raising/lowering the bar for one group relative to another, and b) both groups have a significant number of members near the cutoff. As an example of the type of bias this test would detect, consider U-Michigan's point system [1]. An extra +1.0 GPA was added to black applicants. I.e. an Asian person with 3.9 GPA and black person with 2.9 GPA were equivalent. This would result in Asian people having a higher min GPA than black people. [1] They replaced the point system with vague human heuristics when the supreme court said point systems can't be racist, but vague heuristics can.

by nkurz 11y ago

yummyfajitas 11y ago

My definition is the same as yours - it's exactly about the existence of rejected women who are better than accepted men. This particular test is terrible for VC since the min return in VC will always be zero. But if you build a noise-sensitive version for something like college admissions, what needs to be true is a) bias manifests as raising/lowering the bar for one group relative to another, and b) both groups have a significant number of members near the cutoff. As an example of the type of bias this test would detect, consider U-Michigan's point system [1]. An extra +1.0 GPA was added to black applicants. I.e. an Asian person with 3.9 GPA and black person with 2.9 GPA were equivalent. This would result in Asian people having a higher min GPA than black people. [1] They replaced the point system with vague human heuristics when the supreme court said point systems can't be racist, but vague heuristics can.