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-(Note that we can already basically do this for _images_ of female and male faces, using the [latent spaces found by generative adversarial networks]() and [autoencoders](),
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-Doing it for _actual whole people in the real world_ and not just flat images is a task for future superintelligences, not present-day GANs, but some of same basic principles should apply.)
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-[TODO: Mathematically,
-Joel et al. and response—maybe in next paragraph
-Beyond the Binary: https://www.pnas.org/content/112/50/15468
-http://cogprints.org/10046/1/Delgiudice_etal_critique_joel_2015.pdf
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-> once you draw a boundary around a group, the mind starts trying to harvest similarities from the group. And unfortunately the human pattern-detectors seem to operate in such overdrive that we see patterns whether they're there or not; a weakly negative correlation can be mistaken for a strong positive one with a bit of selective memory.
-https://www.lesswrong.com/posts/veN86cBhoe7mBxXLk/categorizing-has-consequences
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-96.8% classification from MRI https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374327/
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-[the wrists: http://unremediatedgender.space/papers/yune_et_al-beyond_human_perception_sexual_dimorphism_in_hand_and_wrist_radiographs.pdf]