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Attacking discrimination with smarter machine learning

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Re: Attacking discrimination with smarter machine learning

#131

Post by ihsw »

tptacek wrote: post #118
ihsw wrote: post #76

Earlier quoted context omitted.

What's wrong with encoding the status quo? Why do we have to encode progressive extremism into computer models? Being progressive for the sake of "going forward" sounds like misguided idealism. What do we do when progressive computer models lead us down a harmful path, do we simply play the typical liberal blame game and point fingers everywhere else while digging our head into sand?

I'm not sure you're following my point. Conservatives should be no happier than liberals about the prospect of a deeply imperfect status quo being baked into future decisionmaking, because there's much about the status quo conservatives don't like either. This isn't even remotely far-fetched. If you're a rural working class person, it's not at all hard to see how machine learning algorithms could adversely affect dec…

I do understand the point you're making -- my concern centers around deeply flawed models being used despite their shortcomings because their inherently progressive slant is sacrosanct. They would instead be held up and fingers pointed elsewhere, either due to lack of data or incorrect usage of the resulting advice derived from existing bodies of data (or something more sinister, eg: sabotage by opposition parties).

What I'm trying to say is correcting discrimination under the guise that it's unfair to certain sections of society is chasing your own tail out of boredom -- what's the point? To improve society, or improve usefulness of machine learning-derived data to make radical (but necessary) decisions? Do we maintain our objectivity and move away from "improving society" when it's found to be counter-productive, or do we keep going forward with improving society and hope things get better?

Trying to "break out of the status quo" to produce more a accurate representation of the world sounds great, I'm totally all for removing human biases, but my concern is that it'll be handled badly to mistakenly attempt to benefit certain classes of society (eg: repeat of subprime mortgage crises from 07-09 but much more difficult to diagnose).

Re: Attacking discrimination with smarter machine learning

#132

Post by Retric »

striking wrote: post #129
Retric wrote: post #121

Earlier quoted context omitted.

Interesting you said poor, at the time he had over 6 million in a trust fund and stood to inherent vastly more. Some people change their minds because of the community service vs. prison but some don't. PS: PCP has a reputation as a rural poor white persons drug. I wonder if you would have had a different impression if I started by saying he got community service.

Look, if we're talking about assumptions, we're talking about probability. I have no idea who you're talking about. I'll happen upon some statistics once in a while, but otherwise will avoid making assumptions because I simply don't know. You asked me for what I'd say was most statistically probable, you got it. I assume you mean "PCP" and not what circuit boards are printed on, yeah. You're right, I've never heard o…

No, people assume poor people are less likely to get community service after assaulting police officers.

Further, you pulled poor from thin air so you did make an assumption without evidence.

Re: Attacking discrimination with smarter machine learning

#133

Post by tptacek »

ihsw wrote: post #131
tptacek wrote: post #118

Earlier quoted context omitted.

I'm not sure you're following my point. Conservatives should be no happier than liberals about the prospect of a deeply imperfect status quo being baked into future decisionmaking, because there's much about the status quo conservatives don't like either. This isn't even remotely far-fetched. If you're a rural working class person, it's not at all hard to see how machine learning algorithms could adversely affect dec…

I do understand the point you're making -- my concern centers around deeply flawed models being used despite their shortcomings because their inherently progressive slant is sacrosanct. They would instead be held up and fingers pointed elsewhere, either due to lack of data or incorrect usage of the resulting advice derived from existing bodies of data (or something more sinister, eg: sabotage by opposition parties).…

I'm not sure you understand my point, because you keep talking about "progressive slant", and I keep trying to explain to you that ML is going to be just as hard --- in fact, probably far harsher --- on "red state" voters.

Think of it in terms of survival bias. ML models that discriminate against the well-educated urban workers that design and deploy them are not going to make it to production if they obviously discriminate against their own designers. Those developers and "data scientists" are not going to notice if those same models happen to deny college admission to kids who took a year off after graduating to work at a factory to help pay for their siblings room and board.

Re: Attacking discrimination with smarter machine learning

#134

Post by ihsw »

tptacek wrote: post #133
ihsw wrote: post #131

Earlier quoted context omitted.

I do understand the point you're making -- my concern centers around deeply flawed models being used despite their shortcomings because their inherently progressive slant is sacrosanct. They would instead be held up and fingers pointed elsewhere, either due to lack of data or incorrect usage of the resulting advice derived from existing bodies of data (or something more sinister, eg: sabotage by opposition parties).…

I'm not sure you understand my point, because you keep talking about "progressive slant", and I keep trying to explain to you that ML is going to be just as hard --- in fact, probably far harsher --- on "red state" voters. Think of it in terms of survival bias. ML models that discriminate against the well-educated urban workers that design and deploy them are not going to make it to production if they obviously discr…

That is actually a good analogy. Thank you for that.

Re: Attacking discrimination with smarter machine learning

#135

Post by striking »

Retric wrote: post #132
striking wrote: post #129

Earlier quoted context omitted.

Look, if we're talking about assumptions, we're talking about probability. I have no idea who you're talking about. I'll happen upon some statistics once in a while, but otherwise will avoid making assumptions because I simply don't know. You asked me for what I'd say was most statistically probable, you got it. I assume you mean "PCP" and not what circuit boards are printed on, yeah. You're right, I've never heard o…

No, people assume poor people are less likely to get community service after assaulting police officers. Further, you pulled poor from thin air so you did make an assumption without evidence.

Poor people are more likely to commit street crime.

> Findings on social class differences in crime are less clear than they are for gender or age differences. Arrests statistics and much research indicate that poor people are much more likely than wealthier people to commit street crime.

> [...] most criminologists would probably agree that social class differences in criminal offending are “unmistakable” (Harris & Shaw, 2000, p. 138).

http://catalog.flatworldknowledge.com/bookhub/reader/3064?e=...

And again, as you admitted, PCP has the connotation of being used by poor people. I can't find stats on it right now, having just run out of time, but you even admitted it directly.

I didn't pull it out of thin air.

Re: Attacking discrimination with smarter machine learning

#136

Post by [deleted] »

dragonwriter wrote: post #45
tjic wrote: post #32

Earlier quoted context omitted.

> despite the fact that the status quo is informed in large part by structural injustices. This is presented as if it's an unambiguous fact, when it's largely a political stance.

It's an unambiguous fact that the status quo is shaped heavily be many generations of de jure discrimination including chattel slavery and continting structural inequalities in political power that still exist that were designed to protect those other unequal institutions. It's a subjective political view that any or all of those things are injustices, of course, since justice is a subjective thing.

[deleted]

Re: Attacking discrimination with smarter machine learning

#137

Post by powertower »

tptacek wrote: post #127
tjic wrote: post #125

Earlier quoted context omitted.

chronic6l has a wealth of peer-reviewed science on his side, tptacek. While I imagine that most of us think it would be nicer if all subgroups had the same mean attributes, that's not the world we live in and we shouldn't turn our backs on science and embrace faith-based arguments, no matter how nice the motivations.

No, he doesn't. He has a mixture of early Jensenist psychometric research that has been superseded, and neo-phrenologists like Rushton that have been discredited. But of course it's easy to drop little bombs like this into threads and put the onus on other people to explain the science. That's what makes it trolling. Whatever snappy response you have for this, please spare us. There is a reason "the subject of racial…

We do know that heredity/genetics plays a major role in your physical structure - giving you everything from having two arms and two legs, to making you susceptible to some types of cancer.

And there have been many many studies, using millions of subjects, twins, various racial groups, etc, that show the same correlation on your non-physical aptitudes (and their ranges).

The fact is if you sample the different racial groups, it will not even matter where they are and what the history of that location is [1], nor what social-economic class they fall into, the aptitude result will be the same.

The environment does play a role, but the range of that role is already predetermined.

Even the studies that dispute this in their summaries, show this in their data.

So lets not bring political speak into machine learning.

[1] Checking on this factor would be the best way to make sure that discrimination is not playing a role - in influencing the output of machine learning.

Re: Attacking discrimination with smarter machine learning

#138

Post by tptacek »

powertower wrote: post #137
tptacek wrote: post #127

Earlier quoted context omitted.

No, he doesn't. He has a mixture of early Jensenist psychometric research that has been superseded, and neo-phrenologists like Rushton that have been discredited. But of course it's easy to drop little bombs like this into threads and put the onus on other people to explain the science. That's what makes it trolling. Whatever snappy response you have for this, please spare us. There is a reason "the subject of racial…

We do know that heredity/genetics plays a major role in your physical structure - giving you everything from having two arms and two legs, to making you susceptible to some types of cancer. And there have been many many studies, using millions of subjects, twins, various racial groups, etc, that show the same correlation on your non-physical aptitudes (and their ranges). The fact is if you sample the different racial…

Do you have something to say about computer science, or is your sole comment in a thread about machine learning research going to be first-principles race trolling? Comments like these appear literally to be the only kind you write on HN. There must be a better place for you to talk politics than here.

Re: Attacking discrimination with smarter machine learning

#139

Post by Retric »

striking wrote: post #135
Retric wrote: post #132

Earlier quoted context omitted.

No, people assume poor people are less likely to get community service after assaulting police officers. Further, you pulled poor from thin air so you did make an assumption without evidence.

Poor people are more likely to commit street crime. > Findings on social class differences in crime are less clear than they are for gender or age differences. Arrests statistics and much research indicate that poor people are much more likely than wealthier people to commit street crime. > [...] most criminologists would probably agree that social class differences in criminal offending are “unmistakable” (Harris &…

As to connotation's, that's faulty reasoning. The only correct response to any of my questions was, not enough information. Yet, you where more than happy to try and both pick a response and then justify it. Even when I directly said you were wrong.

Now, the same identical reasoning happens all over the place in the criminal justice system. Making the link between crime statistics and crimes almost meaningless. Arrest statistics are just that arrest statistics and they don't tell you about who was actually committing crimes.

PS: I suspect you feel very confidante about his race, except I never confirmed or denied your assumption.

Edit: TLDR; Making a judgement with limited evidence is a really bad habit. People soon forget they chose something because it was slightly better odds and reinforce the judgement so something that may have been even odds to start with often feels much more likely over time.

Re: Attacking discrimination with smarter machine learning

#140

Post by idanoeman »

tptacek wrote: post #116
hajile wrote: post #102

Earlier quoted context omitted.

Women's healthcare costs several times more than mens over their lifetime (and that's before factoring in pregnancy). Countries are just fine "equalizing" that even though that means that men pay way more for their health insurance than they should have to. How many people complain about this happening? Collectivism is just fine when you are the one on the receiving end. Either we set absolute lines of discrimination…

Generally we're most of us in society pretty comfortable with paying for the continuation of the species. There are exceptions to every rule, of course; some of us (not including me) are unhappy we pay to pave the streets, too.

I don't think that we need to be subsidizing babies when the world population is 7.4 billion.
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