[arcticfox]

Consider a 90% free throw shooter vs. a 50% shooter. To get the job, you have to make 3 shots. But the 90% shooter gets 3 shots and the 60% shooter gets 5 shots. All of a sudden the 60% shooter is more likely to get the job.

It highly depends on the details of the interview process, which I don't know, but just to discount it with that logic is impossible.

[AlexandrB]

This analogy doesn't work at all. 3/3 shots is 100% success rate whereas 3/5 shots is 60% - you're literally describing lowering the bar for the 60% shooter.

Additional rounds of interviews are more like trying to accurately diagnose a condition using multiple different tests because the initial test is known to have poor sensitivity and will produce false negatives. Doing multiple rounds may, of course, increase the chance of false positives (reduce specificity); but the assumption in this case is that when hiring minorities the sensitivity of the interview process is much worse than the specificity.

[arcticfox]

Right, that's why I said it depends on how the interview process is done. Some companies do thumbs up / down by round.

On a reread, Damore actually implies that Google's policies as applied to their interview process are "decreasing the false negative rate" for minorities. Whether this is harmfully discriminatory or not is open to opinion, but what I think is clear there is that the statement is favorable and understanding of his minority peers - the policies did not let anyone through who should not have been. I certainly don't think he should be fired for having given that statement.

[hackinthebochs]

I don't see how you don't recognize this as effectively lowering the bar (if not intentionally).

>Additional rounds of interviews are more like trying to accurately diagnose a condition using multiple different tests because the initial test is known to have poor sensitivity and will produce false negatives.

The difference is that what they're testing for isn't a binary proposition (do you have the disease or not), but a spectrum (what is your skill level). Viewing this in terms of false-positives or false-negatives is insufficient. If we think of programming skill as a spectrum, we can ask what is the average top-% of candidates who pass the interview (we might guess its top 5% of all developers). If everyone has the same test then the average top-% is unchanged regardless of any efforts to get more minorities to take the test. But once you start giving more tries to minorities your average top-% necessarily reduces.

Whatever your test is designed to admit (say you're interested in hiring only the top-10% of developers), the average of those who pass will be higher precisely because of the chance factor. Being significantly better than the intended cutoff gives you a better chance at passing and so those who pass skews towards better than the intended cutoff.

I'm not saying whether this is a good or bad thing, but the average skill of those who pass must reduce. It is very straightforward to see this as effectively lowering the bar.

[bduerst]

Your hypothetical is self-fulfilling.

Imagine that if you're a minority, you have nearly a 0% chance of getting hired if you're the only minority in the hiring pool [1]. As an employer, wouldn't you want to counteract that by making sure that the decision to hire/not-hire isn't affected by status-quo bias, so you don't overlook qualified candidates?

https://hbr.org/2016/04/if-theres-only-one-woman-in-your-can...