I think I have just enough language to _start_ to talk about what it would mean. Since sex isn't an atomic attribute, but rather a high-level statistical regularity such that almost everyone can be cleanly classified as "female" or "male" _in terms of_ lower-level traits (genitals, hormone levels, _&c._), then, abstractly, we're trying to take points from male distribution and map them onto the female distribution in a way that preserves as much structure (personal identity) as possible. My female analogue doesn't have a penis (because then she wouldn't be female), but she is going to speak American English like me and be [85% Ashkenazi like me](/images/ancestry_report.png), because language and autosomal genes don't have anything to do with sex.
-The hard part has to do with traits that are meaningfully sexually dimorphic, but not as a discrete dichotomy—where the sex-specific universal designs differ in ways that are _subtler_ than the presence or absence of entire reproductive organs. We are _not_ satisfied if the magical transformation technology swaps out my penis and testicles for a functioning female reproductive system without changing the rest of my body, because we want the end result to be indistinguishable from having been drawn from the female distribution (at least, indistinguishable _modulo_ having my memories of life as a male before the magical transformation), and a man-who-somehow-has-a-vagina doesn't qualify.
+The hard part has to do with traits that are meaningfully sexually dimorphic, but not as a discrete dichotomy—where the sex-specific universal designs differ in ways that are _subtler_ than the presence or absence of entire reproductive organs. We are _not_ satisfied if the magical transformation technology swaps out my penis and testicles for a functioning female reproductive system without changing the rest of my body, because we want the end result to be indistinguishable from having been drawn from the female distribution (at least, indistinguishable _modulo_ having my memories of life as a male before the magical transformation), and a man-who-somehow-magically-has-a-vagina doesn't qualify.
The "obvious" way to to do the mapping is to keep the same percentile rank within each trait, but take it with respect to the target sex's distribution. I'm 5′11″ tall, which [puts me at](https://dqydj.com/height-percentile-calculator-for-men-and-women/) the 73rd percentile for American men, about 6/10ths of a standard deviation above the mean. So _presumably_ we want to say that my female analogue is at the 73rd percentile for American women, about 5′5½″.
You might think this is "unfair": some women—about 7 per 1000—are 5′11″, and we don't want to say they're somehow _less female_ on that account, so why can't I keep my height? But if we refuse to adjust for every trait for which the female and male distributions overlap (on the grounds that _some_ women have the same trait value as my male self), we don't end up with a result from the female distribution.
-The typical point in a high-dimensional distribution is _not_ typical along each dimension individually. [In 100 flips of a biased coin](http://zackmdavis.net/blog/2019/05/the-typical-set/) that lands Heads 0.6 of the time, the _single_ most likely sequence is 100 Heads, but they're only one of those and you're _vanishingly_ unlikely to actually see it. The sequences you'll actually observe will have close to 60 Heads. Each such sequence is individually less probable than all Heads, but there are vastly more of them.
+The typical point in a high-dimensional distribution is _not_ typical along each dimension individually. [In 100 flips of a biased coin](http://zackmdavis.net/blog/2019/05/the-typical-set/) that lands Heads 0.6 of the time, the _single_ most likely sequence is 100 Heads, but there's only one of those and you're _vanishingly_ unlikely to actually see it. The sequences you'll actually observe will have close to 60 Heads. Each such sequence is individually less probable than the all-Heads sequence, but there are vastly more of them. Similarly, [most of the probability-mass of a high-dimensional multivariate normal distribution is concentrated in a thin "shell" some distance away from the mode](https://www.johndcook.com/blog/2011/09/01/multivariate-normal-shell/), for the same reason. (The _same_ reason: the binomial distribution converges to the normal in the limit of large _n_.)
Statistical sex differences are like flipping two different collections of coins with different biases, where the coins represent various traits. Learning the outcome of any individual flip, doesn't tell you which which set the coin came from, but [if we look at the aggregation of many flips, we can get _godlike_ confidence](https://www.lesswrong.com/posts/cu7YY7WdgJBs3DpmJ/the-univariate-fallacy-1) as to which collection we're looking at.
-A single-variable measurement like height is like a single coin: unless the coin is _very_ biased, one flip doesn't tell you much. But there are lots of things about people for which it's not that they can't be measured, but that the measurements require _more than one number_.
+A single-variable measurement like height is like a single coin: unless the coin is _very_ biased, one flip can't tell you much about the bias. But there are lots of things about people for which it's not that they can't be measured, but that the measurements require _more than one number_—which correspondingly offer more information about the distribution generating them.
-Take faces. People are [verifiably very good at recognizing sex from (hair covered, males clean-shaven) photographs of people's faces](/papers/bruce_et_al-sex_discrimination_how_do_we_tell.pdf) (96% accuracy, which is the equivalent of _d_ ≈ 3.5), but we don't have direct introspective access into what _specific_ features our brains are using to do it; we just look, and _somehow_ know. The differences are real, but it's not a matter of any single measurement: [covering up the nose makes people slower and slightly worse at sexing faces, but people don't do better than chance at guessing sex from photos of noses alone](/papers/roberts-bruce-feature_saliency_in_judging_the_sex_and_familiarity_of_faces.pdf).
+Take faces. People are [verifiably very good at recognizing sex from (hair covered, males clean-shaven) photographs of people's faces](/papers/bruce_et_al-sex_discrimination_how_do_we_tell.pdf) (96% accuracy, which is the equivalent of _d_ ≈ 3.5), but we don't have direct introspective access into what _specific_ features our brains are using to do it; we just look, and _somehow_ know. The differences are real, but it's not a matter of any single, simple measurement you could perform with a ruler (like the distance between someone's eyes). Rather, it's a high-dimensional _pattern_ in many measurements you could take with a rule, no one of which is definitive. [Covering up the nose makes people slower and slightly worse at sexing faces, but people don't do better than chance at guessing sex from photos of noses alone](/papers/roberts-bruce-feature_saliency_in_judging_the_sex_and_familiarity_of_faces.pdf).
-Notably, for _images_ of faces, we actually _do_ have magical transformation technology. AI techniques like [generative adversarial networks](https://arxiv.org/abs/1907.10786) and [autoencoders](https://towardsdatascience.com/generating-images-with-autoencoders-77fd3a8dd368) can learn the structure of the distribution of face photographs, and use that knowledge to [synthesize faces from scratch](https://thispersondoesnotexist.com/) and
+Notably, for _images_ of faces, we actually _do_ have magical transformation technology! AI techniques like [generative adversarial networks](https://arxiv.org/abs/1907.10786) and [autoencoders](https://towardsdatascience.com/generating-images-with-autoencoders-77fd3a8dd368) can learn the structure of the distribution of facial photographs, and use that knowledge to [synthesize faces from scratch](https://thispersondoesnotexist.com/) and
[...]
[...]
-Okay. Having supplied just enough language to _start_ to talk about what it would mean to actually become female—is that what I _want_? I mean, I would definitely be extremely eager to _try_ it ...
+Okay. Having supplied just enough language to _start_ to talk about what it would mean to actually become female—is that what I _want_? I mean, if it's reversible, I would definitely be extremely eager to _try_ it ...
-I had said we're assuming away engineering difficulties in order to make the thought experiment more informative about pure preferences, but let's add back one constraint to _force_ the thought experiment to be informative about preferences, and not allow the wishy-washy evasion of "I'm eager to _try_ it."
+I had said we're assuming away engineering difficulties in order to make the thought experiment more informative about pure preferences, but let's add one constraint to _force_ the thought experiment to be informative about preferences, and not allow the wishy-washy evasion of "I'm eager to _try_ it."
What if I can't just "try" it? What if the machine can only be used once? Come up with whatever frame story you want for this: maybe the machine costs my life savings just to rent for two minutes, or maybe the transformation process is ever-so-slightly imperfect, such that you can't re-transform someone who's already been transformed once, like a photocopy being a perfectly acceptable substitute for an original document, but photocopies-of-photocopies rapidly losing quality.
-In that case, if I have to choose—I _don't_ think I want to be Actually Female. I _like_ who I am on the inside, and don't need to change it. So, I guess ... if I'm being honest ... I guess I _want_ to be a normal man wearing a female body like a suit of clothing.
+In that case, if I have to choose ... I _don't_ think I want to be Actually Female? I _like_ who I am on the inside, and don't need to change it. So, I guess ... if I'm being honest ... I guess I _want_ to be a normal man wearing a female body like a suit of clothing.
Is that weird? Is that wrong?
If the magical transformation technology were real, I would want a mirror. (And in the real world, I would probably crossdress a _lot_ more often, if I could pass to myself in the mirror.)
-What's going on here? The sexologist James Cantor [speculates](https://youtu.be/q3Ub65CwiRI?t=281): mirror neurons.
+What's going on here? The sexologist [James Cantor speculates](https://youtu.be/q3Ub65CwiRI?t=281): mirror neurons.
https://www.lesswrong.com/posts/NMoLJuDJEms7Ku9XS/guessing-the-teacher-s-password
[TODO: change scenario to interpolate between people, _at what point_ does it become]
-The thing about Sorites problems is that they're _incredibly boring_. The map is not the territory. The distribution of sand-configurations we face in everyday life is such that we usually have an answer as to whether the sand "is a heap" or "is not a heap", but in the edge-cases where we're not sure, arguing about whether to use the word "heap" _doesn't change the configuration of sand_. You might think that if [the category is blurry](https://www.lesswrong.com/posts/dLJv2CoRCgeC2mPgj/the-fallacy-of-gray), you therefore have some freedom to [draw its boundaries](https://www.lesswrong.com/posts/d5NyJ2Lf6N22AD9PB/where-to-draw-the-boundary) the way you prefer—but [the cognitive function of the category is for making probabilistic inferences on the basis of category-membership](https://www.lesswrong.com/posts/esRZaPXSHgWzyB2NL/where-to-draw-the-boundaries), and those probabilistic inferences can be quantitatively better or worse. Preferences over concept definitions that aren't about maximizing predictive accuracy are therefore preferences _for deception_, because "making probability distributions less accurate in order to achieve some other goal" is the only thing _dece
+The thing about Sorites problems is that they're _incredibly boring_. The map is not the territory. The distribution of sand-configurations we face in everyday life is such that we usually have an answer as to whether the sand "is a heap" or "is not a heap", but in the edge-cases where we're not sure, arguing about whether to use the word "heap" _doesn't change the configuration of sand_. You might think that if [the category is blurry](https://www.lesswrong.com/posts/dLJv2CoRCgeC2mPgj/the-fallacy-of-gray), you therefore have some freedom to [draw its boundaries](https://www.lesswrong.com/posts/d5NyJ2Lf6N22AD9PB/where-to-draw-the-boundary) the way you prefer—but [the cognitive function of the category is for making probabilistic inferences on the basis of category-membership](https://www.lesswrong.com/posts/esRZaPXSHgWzyB2NL/where-to-draw-the-boundaries), and those probabilistic inferences can be quantitatively better or worse. Preferences over concept definitions that aren't about maximizing predictive accuracy are therefore preferences _for deception_, because "making probability distributions less accurate in order to achieve some other goal" is the only thing _deception_ can mean.
That's why defining your personal identity to get the answer you want is cheating. If the answer you wanted was actually _true_, you could just say so without needing to _want_ it.
Imagine my surprise to discover that, in the current year, my weird sexual obsession is suddenly at the center of [one of the _defining political issues of our time_](https://en.wikipedia.org/wiki/Transgender_rights).
-All this time—the dozen years I spent reading everything I could about sex and gender and transgender and feminism and evopsych and doing various things with my social presentation (sometimes things I regretted and reverted after a lot of pain, like the initials) to try to seem not-masculine—I had been _assuming_ that my gender problems were not of the same kind as people who were _actually_ transgender, because the standard narrative said that that was about people whose ["internal sense of their own gender does not match their assigned sex at birth"](https://www.vox.com/identities/21332685/trans-rights-pronouns-bathrooms-sports), and I had never interpreted my beautiful pure sacred self-identity thing as an "internal sense of my own gender",
+All this time—the dozen years I spent reading everything I could about sex and gender and transgender and feminism and evopsych and doing various things with my social presentation (sometimes things I regretted and reverted after a lot of pain, like the initials) to try to seem not-masculine—I had been _assuming_ that my gender problems were not of the same kind as people who were _actually_ transgender, because the standard narrative said that that was about people whose ["internal sense of their own gender does not match their assigned sex at birth"](https://www.vox.com/identities/21332685/trans-rights-pronouns-bathrooms-sports), whereas my thing was obviously a weird sex fantasy—I had never interpreted the beautiful pure sacred self-identity part as an "internal sense of my own gender".
+
+_Why would I?_ In the English of my youth, "gender" (as a single word, rather than part of the phrase "gender role") was understood as a euphemism for _sex_ for people who were squeamish about the hypothetical ambiguity betweeen _sex_-as-in-biological-sex and _sex_-as-in-intercourse. In that language, my "gender"—my sex—is male. Not because I'm necessarily happy about it (and I [used to](/2017/Jan/the-erotic-target-location-gift/) be pointedly insistent that I wasn't), but as an observable biological fact that, whatever my pure beautiful sacred self-identity feelings, _I am not delusional about_.
+
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/2018/Jan/dont-negotiate-with-terrorist-memeplexes/
projects / Ultimately_Untrue_Thought.git / commitdiff