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Not one of the downvoters, but did want to respond to a few points. On peer review: 1) The uploaded version of the preprint that was linked is currently versio

Not one of the downvoters, but did want to respond to a few points. On peer review: 1) The uploaded version of the preprint that was linked is currently version 7. Version 1 did not contain the "this is a peer reviewed article" boiler-plate at the top. It's very possible that GLAAD/HRC saw the original manuscript without this notice. 2) Given that all 7 versions have been posted in the past 9 days, one might reasonably conclude that this is still a work-in-progress and peer review is still currently on-going, (the boilerplate being added in anticipation of the review being completed. Again, the paper is very clearly still being worked on.) On misinformation: Yes I will give you that some of the criticisms might seem over-the-top to the HN crowd, but I think they are understandable given what GLAAD's / HRC's focus is, plus the fact that they aren't addressing "trained scientists." That being said, I don't think their criticisms are completely baseless. I think anyone with technical training, particularly in data analysis / machine learning, is familiar with the phrase: "Garbage In - Garbage Out." And I think it is absolutely correct to point out that maybe if your training data is dating site photos, predominantly of white people in a narrow age range, that you may not have exactly proven your claims that you have "advance[d] our understanding of the origins of sexual orientation and the limits of human perception." That maybe you've just learned some interesting features of current trends in dating site photos. The tragic thing is that both sides (GLAAD & HRC vs. the researchers) claim to care about the privacy and safety of individuals. And kudos to them for thinking of the social implications of this kind of research! (We all know how good phrenology turned out) Because of these implications, I absolutely think it's right for us to question the conclusions of this research (that you can detect sexual orientation from facial morphology, and that this is evidence of the prenatal hormone theory of sexual orientation), given their actual methods (we threw a bunch of dating site photos at a neural-net classifier, and compared to self-reported sexual orientation) All that said, I do think that the paper is likely to be more nuanced than the conclusions reported / the abstract make it out to be (have not finished reading the paper yet). But unfortunately, because of the way science is reported, where the headline is going to be some bombastic "AI can tell if you are gay or straight from just a picture!", there is probably some pressure to voice their criticisms just as loudly.

vadansky 9y ago
>maybe you've just learned some interesting features of current trends in dating site photos. Again, I hate to keep parroting what another HN said, but I hate to see misinformation repeated: >The paper states that they used an existing net, VGG-Face, to exact facial features: https://osf.io/fk3xr/ https://osf.io/fk3xr/ (page 13) >VGG-Face aims at representing a given face as a vector of scores that are as unaffected as possible by facial expression, background, lighting, head orientation, image properties such as brightness or contrast, and other factors that can vary across different images of the same person. All the heavy lifting for this paper was done by logistic regression on the facial features reported by VGG-Face, they didn't train a DNN specifically for identifying sexuality. The algo wouldn't have seen clothing at all. Basically, it's not as simple as "All the gay participants had rainbow flags in the background of their photo so let's ignore this study"
- TFortunato 9y ago
  I never said anything about rainbow flags in the background, nor that we should ignore this study. And fine to be pedantic, it wasn't throwing a bunch of photos at a NN classifier, it was throwing a bunch of photos through a NN to get a descriptor of facial features, then training a logistic regression on that. (Note: they did also train a DNN specifically for this, which they used for example to say things like: "Male facial image brightness correlates 0.19 with the probability of being gay, as estimated by the DNN based classifier. While the brightness of the facial image might be driven by many factors, previous research found that testosterone stimulates melanocyte structure and function leading to a darker skin." which some might argue is quite a jump given the data at hand. What I am saying is that the authors may have been a bit far-reaching in their conclusions, and that "trends in dating site photos" doesn't just mean "is there a rainbow flag present?", but also things like how photos are taken w.r.t angles, and lighting, and retouched, makeup, expressions, etc. (and yes VGG-Face is supposed to be resilient to some of these things, they also used Face++ for studies having to do with morphology, such as using facial contour features. But saying they are resilient to these things and quantifying that are two very different things). To get to even a more fundamental question - Does the population of gay and straight individuals on a dating website necessarily reflect the gay and/or straight populations as a whole? And once the authors start talking about the femininity or masculinity of faces, and whether certain features are gender atypical or not, they are entering very murky and ill-defined territory, which the authors even acknowledged when relating previous results on this front. To be very clear about it: I am not saying that the study should be ignored completely, or that there were no interesting findings. Quite the contrary! What I am saying is that the conclusions being reached ("Our results provide strong support for the PHT, which argues that same gender sexual orientation stems from the underexposure of male fetuses and overexposure of female fetuses to prenatal androgen responsible for the sexual differentiation of faces, preferences, and behavior") are quite a bit of a leap from what was found in the research given the input data and methods, and I think should have been more accurately reported as: "interesting differences in social media photographs of gay vs straight individuals.", with a little less speculation by the authors on what might be causing these differences.

vadansky 9y ago

>maybe you've just learned some interesting features of current trends in dating site photos. Again, I hate to keep parroting what another HN said, but I hate to see misinformation repeated: >The paper states that they used an existing net, VGG-Face, to exact facial features: https://osf.io/fk3xr/ https://osf.io/fk3xr/ (page 13) >VGG-Face aims at representing a given face as a vector of scores that are as unaffected as possible by facial expression, background, lighting, head orientation, image properties such as brightness or contrast, and other factors that can vary across different images of the same person. All the heavy lifting for this paper was done by logistic regression on the facial features reported by VGG-Face, they didn't train a DNN specifically for identifying sexuality. The algo wouldn't have seen clothing at all. Basically, it's not as simple as "All the gay participants had rainbow flags in the background of their photo so let's ignore this study"

TFortunato 9y ago
I never said anything about rainbow flags in the background, nor that we should ignore this study. And fine to be pedantic, it wasn't throwing a bunch of photos at a NN classifier, it was throwing a bunch of photos through a NN to get a descriptor of facial features, then training a logistic regression on that. (Note: they did also train a DNN specifically for this, which they used for example to say things like: "Male facial image brightness correlates 0.19 with the probability of being gay, as estimated by the DNN based classifier. While the brightness of the facial image might be driven by many factors, previous research found that testosterone stimulates melanocyte structure and function leading to a darker skin." which some might argue is quite a jump given the data at hand. What I am saying is that the authors may have been a bit far-reaching in their conclusions, and that "trends in dating site photos" doesn't just mean "is there a rainbow flag present?", but also things like how photos are taken w.r.t angles, and lighting, and retouched, makeup, expressions, etc. (and yes VGG-Face is supposed to be resilient to some of these things, they also used Face++ for studies having to do with morphology, such as using facial contour features. But saying they are resilient to these things and quantifying that are two very different things). To get to even a more fundamental question - Does the population of gay and straight individuals on a dating website necessarily reflect the gay and/or straight populations as a whole? And once the authors start talking about the femininity or masculinity of faces, and whether certain features are gender atypical or not, they are entering very murky and ill-defined territory, which the authors even acknowledged when relating previous results on this front. To be very clear about it: I am not saying that the study should be ignored completely, or that there were no interesting findings. Quite the contrary! What I am saying is that the conclusions being reached ("Our results provide strong support for the PHT, which argues that same gender sexual orientation stems from the underexposure of male fetuses and overexposure of female fetuses to prenatal androgen responsible for the sexual differentiation of faces, preferences, and behavior") are quite a bit of a leap from what was found in the research given the input data and methods, and I think should have been more accurately reported as: "interesting differences in social media photographs of gay vs straight individuals.", with a little less speculation by the authors on what might be causing these differences.