--- /dev/null
+Title: Links: Amy Wax Bloggingheads Appearances
+Date: 2021-01-01
+Category: other
+Tags: linkpost, video, Amy Wax
+Status: draft
+
+After watching a [couple of](https://www.youtube.com/watch?v=yLE67Z_YmSA) [her appearances](https://www.youtube.com/watch?v=iURajqpbU3E) on the Glenn Loury show and [one opposite Adam Serwer](https://www.youtube.com/watch?v=h8uEbK83BYM), is it weird if I admit that I find something about Amy Wax _incredibly attractive_? I mean on a spiritual level—as a female intellectual with _no patience_ for the Egregore. No patience!
Notably, for _images_ of faces, we actually _do_ have transformation technology! (Not "magical", because we know how it works.) AI techniques like [generative adversarial networks](https://arxiv.org/abs/1812.04948) 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/)—or [do things like](https://arxiv.org/abs/1907.10786) sex transformation, as demonstrated by the likes of [FaceApp](https://www.faceapp.com/), the _uniquely best piece of software in the world_.
-If you let each pixel vary independently, the space of possible 1024x1024 images is 1,048,576-dimensional, but the vast hypermajority of those images aren't photorealistic human faces. Letting each pixel vary independently is the wrong way to think about it: changing the lighting or pose changes can change a lot of pixels in what we would regard as images of "the same" face. Instead, our machine-learning algorithms learn a [compressed](https://www.lesswrong.com/posts/ex63DPisEjomutkCw/msg-len) representation of what makes the tiny subspace (relative to images-in-general) of _faces in particular_ similar to each other, and that [latent space](https://towardsdatascience.com/understanding-latent-space-in-machine-learning-de5a7c687d8d) is a lot smaller—say, 512 dimensions.
+If you let each pixel vary independently, the space of possible 1024x1024 images is 1,048,576-dimensional, but the vast hypermajority of those images aren't photorealistic human faces. Letting each pixel vary independently is the wrong way to think about it: changing the lighting or pose can change a lot of pixels in what humans would regard as images of "the same" face. So instead, our machine-learning algorithms learn a [compressed](https://www.lesswrong.com/posts/ex63DPisEjomutkCw/msg-len) representation of what makes the tiny subspace (relative to images-in-general) of _faces in particular_ similar to each other, and that [latent space](https://towardsdatascience.com/understanding-latent-space-in-machine-learning-de5a7c687d8d) is a lot smaller—say, 512 dimensions.
-[TODO: separating hyperplane / Face editing with Generative Adversarial Networks: https://www.youtube.com/watch?v=dCKbRCUyop8 ]
+[TODO: separating hyperplane / Face editing with Generative Adversarial Networks: https://youtu.be/dCKbRCUyop8?t=1433 ]
[...]
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 an outgrowth of my weird sex fantasy—I had never interpreted the beautiful pure sacred self-identity thing 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_.
+_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 potential ambiguity betweeen _sex_-as-in-biological-sex and _sex_-as-in-intercourse. (Judging by this blog's domain name, I am not immune to this.) 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_.
/2018/Jan/dont-negotiate-with-terrorist-memeplexes/
https://www.fast.ai/2020/10/28/code-of-conduct/
"World Rugby Bars Transgender Women, Baffling Players" https://www.nytimes.com/2020/10/26/sports/olympics/world-rugby-transgender-women.html
+
+> And we're all in the same epistemic trap, and we can only see the propaganda a level below ours, and the correct response to seeing others being manipulated is sympathy and horror about the propaganda that _you_ don't see.
+>
+> —[Eli Tyre](https://twitter.com/EpistemicHope/status/1320901905371992064)
+
+kayfabe: https://www.edge.org/response-detail/11783
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