What to data scientists think about race realism...

James Watson got black listed for suggesting that evolution applies to black people, but obviously he's a biochemist, not a data scientist

standard practice in most fields

not chinks, poos

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Why would he be black listed for that? Isn't it common knowledge/belief that modern humans are a result of evolution?

Think about how delicately the Bell Curve treated this subject. Charles Murray is still attacked reputationally and physically to this day for it.

dude wat science isn't like a bunch of pure priests or something. It's just like any other job. It's all full all the same social cliques and rightthink and power games and how to get funding and everything else.

Lefties believe that evolution happened but stopped after our first black ancestor was born. Everything since then is a social construct.

That definitely isn't the standard. I am not sure why you are claiming it is.

Believe it or not, Data Science isn't mainly used to try and justify the racial bias of Jow Forums.

All of science is delayed by incorrect a priori assumptions. Cancer biology was held up for decades by stuborm refusal to give up on the now defunct "cancer is the activation of dormant retroviruses" model. Of course, there's only so much we can do to correct for this, you can't experiment without assumptions at all. As far as race realism goes, anyone smart enough to prove it is smart enough to know that they don't need to.

That's not what I'm saying, im just surprised that people would stunt progress of research in order to keep a narrative in fact. This procrastination will just make it harder for people to cope with if the knowledge is ever released in the future.

He suggested that blacks are more stupid because of divergent evolution with other races, which is actually true, but discussibg it is verboten.

The thing is, there's nothing to gain. Suppose perfect proof of niggers being genetically predisposed to significantly lower IQ and higher aggression appeared in your hand. What would you do with it? Half the people already know it, the other half will deny you. Now imagine if it cost time, money, and maybe your career to produce. Would you still do it? Probably not.

I assumed by "data science", he was talking about actual scientists, not marketing computer engineers

They employ the data scientists, silly. Just like political campaigns and every other damn thing in the world that can leverage its target audience.

Do you not understand what a vendor is?

If it aint bioinformatics, it can fuck right off

the more honest data scientists are already redpilled:

logicmag.io/01-interview-with-an-anonymous-data-scientist/

I'm reminded a bit of Cathy O'Neil's new book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016). One of her arguments, which it seems like you're echoing, is that the popular perception is that algorithms provide a more objective, more complete view of reality, but that they often just reinforce existing inequities.

That's right. And the part that I find offensive as a mathematician is the idea that somehow the machines are doing something wrong. We as a society have not chosen to optimize for the thing that we're telling the machine to optimize for. That's what it means for the machine to be doing illegal things. The machine isn't doing anything wrong, and the algorithms are not doing anything wrong. It's just that they're literally amoral, and if we told them the things that are okay to optimize against, they would optimize against those instead. It's a frightening, almost Black Mirror-esque view of reality that comes from the machines, because a lot of them are completely stripped of—not to sound too Trumpian—liberal pieties. It's completely stripped.

lel

They're not “politically correct.”

They are massively not politically correct, and it's disturbing. You can load in tons and tons of demographic data, and it's disturbing when you see percent black in a zip code and percent Hispanic in a zip code be more important than borrower debt-to-income ratio when you run a credit model. When you see something like that, you're like, “Ooh, that's not good.” Because the frightening thing is that even if you remove those specific variables, if the signal is there, you're going to find correlates with it all the time, and you either need to have a regulator that says, “You can use these variables, you can't use these variables,” or, I don't know, we need to change the law.

As a data scientist I would prefer if that did not come out in the data. I think it's a question of how we deal with it. But I feel sensitive toward the machines, because we're telling them to optimize, and that's what they’re coming up with.

So I'm a fairly experienced data scientist in silicon valley, who came out of a hard science background.
It's kind of like a little personal hell, when you have knowledge from /pol and an ability to drill through anything for an answer, while being surrounded by left wing cultists.
At several conferences there have been remarkably absurd sessions held on how to deal with 'implicit bias' in algorithms and it makes me want to eat a gun.

I went this path because of how much I like truth. For the most part the racial stuff is still in the background but it's bubbling up due to more or less every business using user profiling to some degree. I'm just hoping I can somehow use these skills in a more traditional setting someday without the craziness.

Just have to use feature spaces so latent that humans can't easily interpret them. Then nobody can tell that the computer is being racist.

implicit bias is an issue in developing algos though. I'm not talking about racial bias. Why does everyone on Jow Forums seem to think that ML is purely trying to investigate trends in IQ between races

Working Data scientist.

Working on business data primarily so take everything with a grain of salt. what almost everyone seems to miss about "data science" is that data has to be thoroughly validated and assumptions laid out clearly.

So if you say look at race and poverty in the raw it looks pretty ratialy divided. but you need to consider asumptions. and boy are there assumptions in ratial datasets. the most prominent are Ingranded societal racism, and africa's poor geographic situation leading to low standing socio-economically.

the question is unanswerable because the assumptions just keep piling up. and you come back to the same issue of: data only represents the past state. if the past was racist the data is racist.

I'm working on an algorithm that learns to fit models using everything other than race and IQ. They're paying me big bucks to come up with believable alternate explanations for why things are the way they are.

It has nothing to do with the algorithm you fucking retard, we are being told to only use 'algorithms' with predefined outputs.

lol, who are they?

Why are you working on such terrible projects?

>africa's poor geographic situation leading to low standing socio-economically
What sort of stupid assumption is this?

they work in (((tech))) they either lie to themselves so they can keep a job or hide their beliefs

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You shouldn't invest your labour for those who don't deserve it.

I wouldn't even consider projects like this.

I ain't telling. They think it's actually to do with AI; basically how to chose among the most plausible explanations so as to develop a consistent worldview in a more abstract space.

But most scientists are dumb and don't bother to pay attention to who is funding each individual piece of the puzzle for what ulterior use.

Here's a day in the life of a data scientist
>8AM Wake up
>9AM Spend 1 hour collecting unbelievably lucrative demographic data from a variety of government, survey, and social media sources
>10AM Throw away 90% of your data because it will upset the HR department
>10:30AM Spend 7 hours frantically creating vague and meaningless reports and consulting directives for your clients and hope that the WallStreet autismbux keep flowing in to prop up your dying and pointless industry

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>98% of data scientists are chinks, they don't need bleeding edge statistical analysis to know that niggers are shit
kek

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Some people in the thread are confusing industry/academic data science.

Industry is the one that /pol needs to be mainly concerned with. I have stayed out of the advertising/finance area and worked basically in healthcare, but the prof. conferences (as opposed to academic) are much worse. This is where they just pack rooms full of people and basically 're-engineer' what you learn in the phd, and how it's more important to create healthy outcomes rather than optimized algos, so tweak things here and there to make sure everyone is equal.

If I were tasked with that problem they'd probably tell me to rip race out of the variables. There are a lot of factors that would come into play, but if you made it the class variable it would probably do a very good job guessing race

Anyone got a CSV?

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that's boring though.

If you're gonna do healthcare then at least do medical imagery

Fuck yeah. If I could get those asshats for like minimum wage to maybe $9 an hour.

Totally base a company off that.

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Lmao.
>Get rich
>Fuck the ethics
>Get recruited by the NWO because youre so badass
Trust me nigger. Feels good to be king

Remember Jason Richwine? Nicholas Wade?