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Are you flat out saying that some races and sexes are not intelligent enough to be in the tech industry?
by doorstar 6y ago
Are you flat out saying that some races and sexes are not intelligent enough to be in the tech industry?
- user982 6y agoThey also said that non-white races look too alike for facial recognition: https://news.ycombinator.com/item?id=23462568 https://news.ycombinator.com/item?id=23462568
- doorstar 6y agoAh, a kook. Good to know, thanks
- zozbot234 6y agoThey didn't say "they all look alike", they said that white faces have more contrast so are easier to differentiate even with a naïve CV algorithm. It's one more source of systemic bias in the ML literature, especially given the comparative scarcity of source data from non-majority groups.
- user982 6y ago> It's one more source of systemic bias in the ML literature, especially given the comparative scarcity of source data from non-majority groups. centimeter's posts in that thread directly reject your proffered line of thought: > your training data does not have enough people with dark skin or African American face features This isn’t the issue - the issue is lower variance across black faces in any basis.
- centimeter 6y agoHere's what I said: "if you partitioned the faces by race the output of the SVD would be much wider for white people [...] white people have more light/dark contrast, more hair colors, more eye colors, etc.". This is an obvious fact that is widely recognized by CV practitioners.
- runawaybottle 6y agoYou’re just asking for a long drawn out fight over which cultures emphasize education more.
- doorstar 6y agoScratch out race. Are you flat out saying that some sexes are not intelligent enough to be in the tech industry?
- runawaybottle 6y agoI’m not the OP, but I doubt anyones saying that. If anything you’re asking for a long drawn out fight over why some sexes don’t major in STEM more. The argument is going to boil down to the “pipeline” problem, ‘there’s not enough to begin with for it to be represented in proportion’, which leads to the moral hazard dilemma of do we just started filling quotas. Edited
- doorstar 6y agoThe OP has clarified that he thinks that women inherently do not have the skills needed for the tech industry. It's not an unusual attitude, and challenges your assessment that this is a 'pipeline' problem. As long as tech workers think that some races have 'cultural' problems and as long as some tech workings think that there are differences between men's and women's brains that make women less suited for tech work, I think we have to stop dismissing this as a pipeline problem. The prejudice is real and all over this thread posters are happily justifying it.
- centimeter 6y agoYou should try to learn how to discern the difference between “<group> doesn’t have the skills for <activity>” and “<group> is statistically less likely to match selective criteria of <activity>”. It’s a pretty critical distinction.
- 6y ago
- centimeter 6y agoNo, but I am saying that there are differences in population-level intelligence distributions across groups. The data is pretty clear on this.
- doorstar 6y agoI'm not sure I understand the distinction. If there are differences in 'population-level' intelligence, then some populations are less intelligent, correct? If some populations are less intelligent, then it is OK to not hire them in the tech industry. In your opinion, how do you tell the less intelligent populations from the more intelligent populations?
- zozbot234 6y agoYou can't use statements about populations to draw inferences about individuals - and we hire individuals, not populations. Your entire framing of this issue is 100% backwards.
- centimeter 6y agoIf you use population-level characteristics to make blanket individual-level determinations, you are an idiot.