Artificial Intelligence's White Guy Problem
nytimes.com
nytimes.com
Also, trust me i can talk about this because i'm not white...
fact - people prefer people like them. Not even consciously, this is basic shit hardwired into us. I don't blame white men for being subconsciously biased to hiring white men, literally any other group would do the same. sure we can try to fight that bias, but its not at all evil or wrong to have that bias, only natural.
fact - taking an "agnostic" approach the way science does, of course the algorithms will reflect "biases". if men are statistically more likely to be programmers, or black people are more likely to commit crimes (STATISTICALLY), then the algorithm will pick that up. They are biases sure, but also statistical realities.
Now we can debate whether we should actively engineer algorithms to fight these "biases" on a case-by-case basis (for example, focusing more on women might be a win if you can find talent no one else can), but there's no reason to start pointing fingers at the "evil white guys" on top who planned this from the very beginning... it's just more stereotyping.
hypothesis - she wrote this crap to gain publicity.
I do agree with the article that feeding biased data will result in a biased system and we need to be aware of that. But calling it racist and sexist is sensationalism.
I think you meant black people are more likely to be convicted of crime. The problems with crime 'statistics' is that on the surface, it all seems coldly scientific, yet they are generated and derived via very biased, very human, very unscientific processes - there is a lot of bad data. The ACLU did research that showed that there is no statistically significant difference in the possession of weed between white and black people, yet more black people are convicted[1] for possession.
Here's a mind experiment: after watching this YouTube video[2], how skewed do you think the statistics for white female criminals (bike thieves) vs black criminals would be?
1. https://www.aclu.org/files/assets/aclu-thewaronmarijuana-rel...
I just think we need to be able to TALK about these issues, so that when a real expert looks at those statistics they can get to the truth of the matter, and say that truth whether it is or isn't politically correct.
The law says racism is illegal in certain situations, and society says racism is undesirable in most situations.
The law and society aren't claiming that racism is statistically non-optimal -- in fact, there are lots of things more optimal than status quo that many people would find totally horrifying.
If are widely replacing human systems with AI systems, I think this is a legitimate concern.
I really depart from the article in two areas:
1. The AI will inherit the biases of its creators. This is possible but far from guaranteed. And relatedly, inclusivity of the development team guarantees nothing regarding the goals of the system.
2. Criticising the people who are warning of the problem and trying to do something about it. This is related to the AI control problem. There is no switch that can be flipped that will prevent AI systems from Bad Ideas. It's not that we just aren't flipping it to preserve our chokehold on captialism. Implementing morality in AI systems is a genuinely monumental problem. And the people who are doing something about it are behaving very altruistically.
And with AI, we must make these values explicit, which is very difficult to do - i agree this is a very important problem to solve, and the people doing it should absolutely be rewarded.
Honestly, reading the article again after your summary i found it very reasonable :p I think the headline just ticked me off.
No one is stopping other people from getting in on the debate, they absolutely should (and I'm sure there are roadblocks in their way, and people who really are racist). It just feels wrong to implicitly all the "bad white people" for that. Blame those who cause the problem. Otherwise we are back to stereotyping.
"The law...". Whose law? "Society says...". Which society? "Implementing morality". Whose morality?
Also, why wouldn't you want things to be optimal, depending what what they're optimizing for? I thought optimizing was the exact point of machine learning and AI.
By society I was thinking of Western society. Wikipedia lists equality as value in 2nd paragraph here: https://en.wikipedia.org/wiki/Western_culture
By morality I was thinking along the lines of socially accepted behaviour in the contemporary United States, and mainstream Christian morality which isn't the official state religion, but in my opinion the basics of it are taken as a given in politics, government, media, and academia.
Overall, I'm referring to mainstream anglo law, society, and morality.
> why wouldn't you want things to be optimal, depending what what they're optimizing for?
The reason is that when you express your goals, you don't fully understand what the consequences will be. There may be consequences that are totally repugnant to you. The child-story level version of this is where you get a genie which gives you your wishes in a horrible way: i.e. I wish to be the richest man in the world, and so the genie kills everyone else. I want a nice big house like my parents, and so the genie kills your parents and you inherit. Et cetera.
Telling the computer to do what you want is notoriously difficult for simple imperative programming, to the point where many people think a large fraction of the population just isn't up to it intellectually, and if you need proof of this you can search for fizz-buzz interview stories. Setting up goals or incentives for a system that behaves in a way the you can barely understand is even more difficult.
They're complaining about Nikon cameras not recognizing Asian faces properly, and this is discrimination? Nikon is a Japanese company. Headquarters is in Tokyo. The CEO is Kazuo Ushida.
But similar errors have emerged in Nikon’s camera
software, which misread images of Asian people as blinking,
I have the nagging sensation that if were up to todays hyper-sensitized media on how society should look and function, we would all be grey globs in a grey world, devoid of any differences.
The more depressing truth? Striking these chords are an absolute goldmine for ratings and clicks. Everyone is naturally curious about how they might be currently oppressed or disadvantaged, it plays to our instinctual tribalism.
So please, realize you can do anything you want in this world, and don't be seduced by hate and bitterness from some writer sitting in Soho that has a click-quota to meet this month.
This article makes a perfectly valid point- AI is only as good as the data you use to train it. If you feed it bad, biased data, then the AI will behave in bad, biased ways.
These biases can be major (no Amazon delivery to black neighborhoods) or minor. I'm reminded of a gaming podcast I heard (can't remember which one) where a guy recounted watching a female journalist try VR goggles that couldn't detect her eyes because she had mascara. Apparently no one making the headset had tested the effects of that kind of makeup.
The article is right. If we are serious about creating products that revolutionize everyone's lives, we need to involve more kinds of people. Our perspectives are limited. We can't understand everything. That's the point of having a diverse team. Like Ben Thompson says, there's a very strong business case for diversity because "You don't know what you don't know."
The whole point of AI and machine learning is to find things that are not immediately obvious but backed up by the data.
The author of this article is suggesting that if the conclusions of this research are politically unfavorable, then there has to be bias/racism/sexism somewhere. race/gender/socioeconomic agnostic.
Which runs immediately counter to both machine learning and research in general. "Dang it, run the numbers until it supports the conclusion I support."
It's like the author doesn't understand the basic premise of machine learning or research. If the datasets are restricted in some way unfairly, that's something to be looked at. Algorithms are generally fair and unbiased.
More policing reduces crime. The author seems to think that people living in these poor, nonwhite neighborhoods would rather see the police resources go to wealthy, white neighborhoods. But the studies show that minorities and people living in high-crime neighborhoods mostly do approve of police. There is a lot of cognitive dissonance here: is crime reduction through more policing in poor nonwhite neighborhoods a right goal despite sometimes justified skepticism of the police or not?
http://www.theatlantic.com/national/archive/2015/02/more-pol...
Equality is about opportunity, not results.
Its much the same way as, say, startups trying to market products to new mothers or highschool students have a hard time because they can't "eat their own dogfood" if they're all late-twenty-something white men. Huge markets lie unserved, I'm sure, because they're demographics that don't tend to produce software engineers or entrepreneurs.
Well, I bet the reason are historical statistics of recidivism, which presumably were used to train these algorithms.
But hey, this is NYT, they cannot simply acknowledge the existence of differences in crime statistics between races, so 'the reason remains unknown'. Hilarious.
https://news.ycombinator.com/item?id=11980557
At least this article has a _slightly_ less hostile title, but the fact remains: it's not white men's fault that they have been innovative and early in the field of AI. If one absolutely must drag identity politics into AI it would be more accurate to say that women should participate more, and that's on them. Not white men.
Regardless, I don't see how being sexist and racist (as these articles are) helps anything.
EDIT: I fully agree with WalterBright below but have been banned by HN from continuing my conversation in this thread for daring to suggest insulting white men might be racist and sexist.
In the D language community, we have many strong contributors who we actually have no idea who they are, other than their online persona that they create themselves.
We don't know their age, race, gender, religion, nationality, politics, nothing.
It's as close to a pure meritocracy as is probably humanly achievable.
You say it's not white men's fault that thy were innovative early in AI. Consider though when the field of AI was first being developed (in the late 50s) which black or people of color in the US would even have had access to the same resources that e.g. John McCarthy had. And why would they have had difficulty accessing those resources? Because of the laws white people had in place then.
So to say that it's white men's fault may be too simplistic, but it also has historical truth.
It's a direct attack on a particular gender and race.
1960 was 56 years ago. It has no relevance on people studying the field today.
Saying that a distance in the past has no relevance on people studying the field today is ridiculous. You're saying "the past has no relevance". Especially considering scale, 56 years is not a long time for things to change. There's ample examples of how what was so socially and politically that affected black people 56 years ago continues to exist today.
EDIT: Since I can't reply anymore, I'll just add my comment here. I (and most people) are in no way responsible for the lack of women in AI. If you personally feel responsible because you know you've been sexist/racist, great, make amends and don't do it anymore. Tossing blame at people you don't know and saying they're responsible for your actions is not the correct course. Blaming white men is racist and sexist so you can take this opportunity to learn and hopefully stop making generalizations about people regardless of their gender or race.