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Comment The obsession with DNS is stupid (Score 1) 14

A good place to see that politicians are generally clueless and incapable or unwilling to see facts. I mean, I can run my own recursive DNS with no problems and the only thing I lose is some performance from caching. There is not even a reasonable possibility to block this in the network.

Comment Funny thing (Score -1) 33

Software Engineering still is not even remotely real engineering. It is too messed up, to chaotic and too clueless about its main object. Hence, no, she cannot have established it as a proper engineering discipline, because it still does not qualify as one.

Seriously, I am getting really tired of some people being lauded all out of proportion just because they were women in tech. I have no problem with them being recognized, but this type of story is just propaganda and deeply dishonest.

Comment No, he did not "calculate".... (Score 1) 111

What he did is make up some "facts" and then throw some math on top to obscure that the "facts" are pure hallucinations. Works on the stupid and is something regularly done today. It does work better when the math used is statistics, because that is hard to really understand even for experts. But, if sone right, you get all kinds of magical symbols and an end-result that _surely_ must be true...

That said, the already started human-made climate change will reduce population, probably pretty strongly. When agriculture stops working in mist places, that tends to have rather strong limiting effects. Hence regulation mechanisms are coming active before things are getting close to the point were only fast collapse is possible. This seems to be an universal property of finite complex systems, such as we have on this planet.

Comment Re: Probably due to methodical errors (Score 1) 201

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.

Comment Re:you cant be serious. (Score 1, Informative) 201

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.

Comment Re: confirmation bias (Score 2, Insightful) 201

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.

Comment Re:mostly mash-ups of existing techniques (Score 1) 114

While they are trained on existing data, they are also capable of reasoning.

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.

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