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I posted this as a reply elsewhere, but I think anyone inclined to believe this model/study supports the prenatal hormone theory should read this from Calling B

I posted this as a reply elsewhere, but I think anyone inclined to believe this model/study supports the prenatal hormone theory should read this from Calling Bullshit: http://callingbullshit.org/case_studies/case_study_ml_sexual_orientation.html http://callingbullshit.org/case_studies/case_study_ml_sexual... The setup and modeling may be perfectly sound, but the conclusions are a big stretch: they didn't control for intentional differences in presentation (the data was dating site photos), nor did they appropriately test for significance of the supposedly subtle facial differences picked up by the model (gay men having more feminine faces, gay women more masculine ones).

vadansky 9y ago
People keep saying this, but as another HN pointed out: 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 by was done 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. It's pretty disturbing how quick people are to dismiss papers that make them uncomfortable, latching onto the first excuse to dismiss it without even confirming if the excuse is valid or not. Clear Cognitive Dissonance in action.
- foldr 9y ago
  They're "unaffected as possible", but not necessarily completely unaffected.
- claytonjy 9y ago
  That's a really important point about this not being a novel DNN, but I'm not sure how it addresses either of the main criticisms from the link I posted. The first is that claiming this methodology outperforms humans is unfair; there's no expectation that Turkers are particularly good at identifying sexuality from photographs, they haven't been able to train in a remotely analogous way, and there's no comparison to "experts" in orientation recognition (if those exist). The second is that the authors of this study use the differences extracted by VGG-Face to claim support for PHT, despite not applying an appropriate statistical test to the differences in the features between groups. This is the bigger scientific misstep in my mind, the willingness to make a strong, apparently controversial claim (I'm not too familiar with PHT or its history) without properly validating it.
  - dspoka 9y ago
    For your second point, what in your opinion would be the right statistical test to apply?

vadansky 9y ago

People keep saying this, but as another HN pointed out: 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 by was done 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. It's pretty disturbing how quick people are to dismiss papers that make them uncomfortable, latching onto the first excuse to dismiss it without even confirming if the excuse is valid or not. Clear Cognitive Dissonance in action.

foldr 9y ago
They're "unaffected as possible", but not necessarily completely unaffected.
claytonjy 9y ago
That's a really important point about this not being a novel DNN, but I'm not sure how it addresses either of the main criticisms from the link I posted. The first is that claiming this methodology outperforms humans is unfair; there's no expectation that Turkers are particularly good at identifying sexuality from photographs, they haven't been able to train in a remotely analogous way, and there's no comparison to "experts" in orientation recognition (if those exist). The second is that the authors of this study use the differences extracted by VGG-Face to claim support for PHT, despite not applying an appropriate statistical test to the differences in the features between groups. This is the bigger scientific misstep in my mind, the willingness to make a strong, apparently controversial claim (I'm not too familiar with PHT or its history) without properly validating it.
- dspoka 9y ago
  For your second point, what in your opinion would be the right statistical test to apply?