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Anecdotally it may exist; statistically, however, it does not.

Let's think about your "female friend" who has lousy technical chops and a 2.5 gpa at a mediocre state university. Is every woman with a 2.5 GPA at a lousy state university getting an interview at all three companies? No? Hmm. I suspect there's something much more to her resume than what you're telling her. These companies are not all simultaneously saying, hey, let's go interview this one woman who happens to have a 2.5 gpa at a crappy school. You're just seeing it that way because you think reverse discrimination is an issue.

Fortunately, this has been studied. And guess what? Equally qualified women have a harder time having their resume selected for technical positions. A similar study was done for black people vs. white people (or, technically, black-sounding names vs. white-sounding names).

It turns out that the conscious thought people have of wanting to hire more women is secondary to their more subconscious bias.

Regarding the overall statistics; I agree, hence what I wrote about there being real discrimination against them. What I intended to claim (but perhaps could have been more clear about) is that women have these out-in-the-open advantages and even more hidden-behind-closed-doors disadvantages.

You seem to be attaching an argument to my statement that I did not intend to convey; I don't think that reverse discrimination is an issue. I think it is extremely visible, and gives you really lousy visible situations like the ones I mentioned that are obvious errors, that doesn't mean that it is a bad idea.

a female friend of mine was able to easily get interviews at Google, Microsoft and Apple every year despite lousy technical chops and a 2.5 GPA at a mediocre state university

There's more to aptitude than GPA and "technical chops". A student who started from zero (as is common for girls in CS) and had a 2.5 GPA after four years would look much more appealing to me than a student who had been programming since they were 12 and had a 3.0 GPA. They're on a steeper trajectory.

And whether you to a "top tier" or a "mediocre" university I don't think says much about your aptitude. I know people who slacked off in world class courses, and I know people who Did The Work at a no-name university, and I know who I would hire.

The trajectory theory is interesting, if two applicants were otherwise similar you would count it against someone for having experience before college? In this case, she was actually someone who took 2 years of computer science in highschool, though her resume didn't say that so so I'm not sure how someone could assess her trajectory that way.

Honestly all of that is irrelevant. What I was actually trying to get at was at the time I was minorly irked (probably just like the guy in this story) due to a perceived unfairness against me due to gender. I've since come to the conclusion that reverse discrimination really is as huge as it seemed then, but that companies are making such big efforts because there is an even larger but less visible bias against women that simply isn't obvious to college kids or even most industry professionals.

The friend's position is totally understandable given the totally different levels of visibility of the two directions of discrimination; that doesn't make him correct.

> Anecdotally it really does exist

You can take just about any conceivable trend and anecdotally "confirm" its existence based on a small enough sample size or the right anecdote. That doesn't mean it is statistically relevant.

And yet when people make decisions, they are much more influenced by anecdotal relevance than statistical soundness. Reminds me of the time when my buddy was trying to get a spot doing research as an undergrad in one of the biochem labs. More than one prof had labs where female undergrads outnumbered the males, so he said he wished he was female so he could "wiggle my ass" to get into a lab.

edit: Also, there are statistics of overall populations and statistics of subpopulations. Sometimes the smaller sample sizes (the subpopulations) are more relevant.

Can you clarify this, are you claiming that reverse discrimination for women in CS doesn't exist? I wasn't aware that there was any question about that; I understand it to be publicly stated policy at all big tech companies. Note that I'm not making a claim that women are more likely to be hired or promoted; as I said there is a lot of discrimination against women that is less visible which is exactly what reverse discrimination is trying to, well, reverse.

I wasn't claiming anything, in terms of whether it does or does not exist.

I was just pointing out that the two anecdotes you presented are merely that. Anecdotes. I see a lot of people on HN making statements like "that claim makes sense to me because [anecdote]," without regard for how representative the sample size is. This is called cherry-picking and is a great way to (unintentionally) reinforce a flawed world view.

It might be true that reverse discrimination in CS is commonly practiced, but your initial statement did nothing in the way of proving or disproving it.

I'm aware of what "anecdotally" means, that is exactly why I qualified my statement with the word "anecdotally".