That wasn't the thing people didn't like about him.

He was wrong for doing a witch hunt, punishing people without due process of law.

If your intent in making the qualifications was to avoid hiring an American, then a judge (or jury) can rule that you broke the law.

that presented themselves as "male" were paid more per task and perceived as more "human-like" than their "female" counterparts

Those complaining loudest are the ones, who can't define the term "woman".

Those are the contractors.

I don't really oppose H1b, but arrest one CEO who is hiring people illegally, and this will stop.

This is true. I like my H1b coworkers (so I definitely won't report anything), but I've never seen a company apply for one in a way that wasn't fraud.

If H1B were really about skilled foreigners filling gaps that can't be filled otherwise, their salaries would be high relative to US citizens.

In a free market, your salary is proportional to how hard it is to replace you:

Push buttons like a trained seal? Peanuts.

Know where to place the the thousand dollar chalk mark? Mid six figures easy.

So what do H1Bs at Microsoft make?

If these links
https://duckduckgo.com/?q=h1b+...
are to be believed, kinda average for a software engineer. Maybe even a little low. Boston area under 160k.

Not the stereotypical monkey pushing a button, but not exactly top flight talent either.

There's no such thing as a 10.

If she shows some tits she'll get paid a lot more than the men.

I just looked at the paper and you are right. Thanks for looking.

The male and the female one are basically suggesting visually that the man is competent and the woman is not. I mean even only the cloth pattern of the skirt that "she" is wearing is atrocious. It is like they made the "woman" intentionally unattractive while they made the "man" average. ("She" is also blonde, of course, while "he" has dark hair.) I have no idea whether this was actually done intentionally, but if I were to design a study to find this type of bias, that is what I would use. I wonder whether they did something similar in the text interfaces.

I also noticed that their names are Johanna and Johan, i.e. a proper male name for "him" and a feminized male name for "her".

So, after all, my first take of "likely methodical error" was correct.

The study is flawed in another way as well because "everybody knows" that women earn less than men. (Usually that is "proven" with the unadjusted wage gap, which is completely bogus and essentially a lie.) Hence the study participants just conformed to what they thought were the facts of the matter. Makes the results completely meaningless.

And the other thing is that "everybody knows" there is a gender pay gap. This is only true for the unadjusted gap, but most people do not know what that means. Once you adjust for factors like experience and field-of-work the difference is below the margin of error, i.e. small and we do not even know whether it is real. We essentially have same wages for the same work and qualification and had it for a while. That some parts of some gender groups decide to not do the same work or invest less or more time into getting experience is a separate problem and not a problem of payment.

Hence the people in this "experiment" were just conforming to what they thought was expected of them. That makes the whole thing bogus. Obviously wages in the real world are determined by a different procedure and harping on about women and men not behaving exactly the same (as a group) is just one thing: counterproductive.

Well, what can an LLM do? It has no understanding or insight, so it cannot see whether something is a good solution or not. Obviously, a smart human would not even have looked for a "solution" like that, because it is obvious crap.

Are you serious? Because that is the dumbest shit I have read in a long, long time.

Since you do not even seem to know the very basics, here is a starting point: https://en.wikipedia.org/wiki/...

No. Or rather not to any meaningful degree or depth. They can do very shallow reasoning only and after a few steps into deeper reasoning chains, only noise is left. Statistical AI is completely unsuitable for automated deduction. It is not even remotely comparable to what a smart human or even the very limited automatic theorem proving systems can do.