Nelson _et al._ also found that when the people in the photographs were pictured sitting down, then judgements of height depended much more on sex than when the photo-subjects were standing. This too makes Bayesian sense: if it's harder to tell how tall an individual is when they're sitting down, you rely more on your demographic prior. In order to reduce injustice to people who are an outlier for their group, one could argue that there's a moral imperative to seek out interventions to get more fine-grained information about individuals, so that we don't need to rely on the coarse, vague information embodied in demographic stereotypes. The _moral spirit_ of egalitarian–individualism mostly survives in our efforts to [hug the query](https://www.lesswrong.com/posts/2jp98zdLo898qExrr/hug-the-query) and get [specific information](/2017/Nov/interlude-x/) with which to discriminate amongst individuals. (And _discriminate_—[to distinguish, to make distinctions](https://en.wiktionary.org/wiki/discriminate)—is the correct word.) If you care about someone's height, it is _better_ to precisely measure it using a meterstick than to just look at them standing up, and it is better to look at them standing up than to look at them sitting down. If you care about someone's skills as potential employee, it is _better_ to give them a work-sample test that assesses the specific skills that you're interested in, than it is to rely on a general IQ test, and it's _far_ better to use an IQ test than to use mere stereotypes. If our means of measuring individuals aren't reliable or cheap enough, such that we still end up using prior information from immutable demographic categories, that's a problem of grave moral seriousness—but in light of the [_mathematical laws_](https://www.lesswrong.com/posts/eY45uCCX7DdwJ4Jha/no-one-can-exempt-you-from-rationality-s-laws) governing reasoning under uncertainty, it's a problem that realistically needs to be solved with _better tests_ and _better signals_, not by _pretending not to have a prior_. This could take the form of _finer-grained_ stereotypes. If someone says of me, "Taylor Saotome-Westlake? Oh, he's a _man_, you know what _they're_ like," I would be offended—I mean, I would if I still believed that getting offended ever helps with anything. (It _never helps_.) I'm _not_ like typical men, I _don't like_ typical men, and I don't want to be confused with them. But if someone says, "Taylor Saotome-Westlake? Oh, he's one of those IQ 130, [mid-to-low Conscientiousness and Agreeableness, high Openness](https://en.wikipedia.org/wiki/Big_Five_personality_traits), left-libertarian American Jewish atheist autogynephilic male computer programmers; you know what _they're_ like," my response is to nod and say, "Yeah, pretty much." I'm not _exactly_ like the others, but I don't mind being confused with them.
Nelson _et al._ also found that when the people in the photographs were pictured sitting down, then judgements of height depended much more on sex than when the photo-subjects were standing. This too makes Bayesian sense: if it's harder to tell how tall an individual is when they're sitting down, you rely more on your demographic prior. In order to reduce injustice to people who are an outlier for their group, one could argue that there's a moral imperative to seek out interventions to get more fine-grained information about individuals, so that we don't need to rely on the coarse, vague information embodied in demographic stereotypes. The _moral spirit_ of egalitarian–individualism mostly survives in our efforts to [hug the query](https://www.lesswrong.com/posts/2jp98zdLo898qExrr/hug-the-query) and get [specific information](/2017/Nov/interlude-x/) with which to discriminate amongst individuals. (And _discriminate_—[to distinguish, to make distinctions](https://en.wiktionary.org/wiki/discriminate)—is the correct word.) If you care about someone's height, it is _better_ to precisely measure it using a meterstick than to just look at them standing up, and it is better to look at them standing up than to look at them sitting down. If you care about someone's skills as potential employee, it is _better_ to give them a work-sample test that assesses the specific skills that you're interested in, than it is to rely on a general IQ test, and it's _far_ better to use an IQ test than to use mere stereotypes. If our means of measuring individuals aren't reliable or cheap enough, such that we still end up using prior information from immutable demographic categories, that's a problem of grave moral seriousness—but in light of the [_mathematical laws_](https://www.lesswrong.com/posts/eY45uCCX7DdwJ4Jha/no-one-can-exempt-you-from-rationality-s-laws) governing reasoning under uncertainty, it's a problem that realistically needs to be solved with _better tests_ and _better signals_, not by _pretending not to have a prior_. This could take the form of _finer-grained_ stereotypes. If someone says of me, "Taylor Saotome-Westlake? Oh, he's a _man_, you know what _they're_ like," I would be offended—I mean, I would if I still believed that getting offended ever helps with anything. (It _never helps_.) I'm _not_ like typical men, I _don't like_ typical men, and I don't want to be confused with them. But if someone says, "Taylor Saotome-Westlake? Oh, he's one of those IQ 130, [mid-to-low Conscientiousness and Agreeableness, high Openness](https://en.wikipedia.org/wiki/Big_Five_personality_traits), left-libertarian American Jewish atheist autogynephilic male computer programmers; you know what _they're_ like," my response is to nod and say, "Yeah, pretty much." I'm not _exactly_ like the others, but I don't mind being confused with them.