4 ms·

Neural nets more accurate than humans at detecting sexual orientation in images

37 points by helloworld 9y ago

helloworld 9y ago
Some additional context and opinion on this: https://www.washingtonpost.com/opinions/ai-gaydar-could-compromise-lgbtq-peoples-privacy--and-safety/2018/02/19/172156bc-126d-11e8-9065-e55346f6de81_story.html https://www.washingtonpost.com/opinions/ai-gaydar-could-comp...
abusoufiyan 9y ago
But why does it matter? What could it possibly be used for? I can't think of a use for this which wouldn't be crossing a line / inappropriate / dangerous.
- JorgeGT 9y ago
  Homosexual relations are illegal in ~70 countries, and punishable by death in ~10 of those, such as Iran, Saudi Arabia, Brunei, Yemen, etc. Governments in these countries could run this software in their databases, rooting out and prosecuting or even executing those identified. So I would say this kind of software merits discussion.
  - barry-cotter 9y ago
    The governments in these countries are evil, not stupid. The false positive rate is too high for this to be useful at anything but a really coarse, maybe check this guy out level. All of the countries you name bar Yemen are easily capable of rooting out and destroying their gay communities if they really wanted to. They don’t. What they want is to make sure everyone involved is very discreet. Hypocrisy is the homage vice pats to virtue etc.
Animats 9y ago
The data used is from dating web sites. That's not a good sample source.
- im3w1l 9y ago
  Maybe not but still impressive that they beat humans, no?
  - krick 9y ago
    Well, assuming the data isn't good — no, obviouly. What "beating humans" would even mean in that case? Imagine you have a dataset of dog and squirrel pictures, with "dog" and "squirrel" (or, actually, "elephant" and "shark") labels assigned quasi-randomly. You make humans and NNs to compete in what label you assigned to them. NN beats humans. Now, what the fuck that result even means?
    - bryanrasmussen 9y ago
      yeah but I guess the data isn't bad in that way in that the sexual orientation of people on the site is probably labeled accurately (in fact I would expect there it's more accurate than, you don't want to lie about what you want on the dating service), the data is bad in that it is perhaps not a representative sample of the population as a whole?
      - im3w1l 9y ago
        > is probably labeled accurately > the data is bad in that it is perhaps not a representative sample of the population as a whole? Yeah that's my thinking too
      - erispoe 9y ago
        What do you mean by labelled accurately? The AI only predicts how an individual self-labelled on a fairly public dating service, not how this person feels or behaves in any other way. There are so many headless torsos on Grindr (or any other gay hookup app) because many men don't want to self label as gay when they look for sex with other men. These men could very well be looking for women on Tinder.
        bryanrasmussen 9y ago
skjerns 9y ago
This is probaly the best article that you need to read after reading another one of those 'detecting sexual orientation with dating profile pictures/prison inmates/etc' papers: https://medium.com/@blaisea/do-algorithms-reveal-sexual-orientation-or-just-expose-our-stereotypes-d998fafdf477 https://medium.com/@blaisea/do-algorithms-reveal-sexual-orie...
erispoe 9y ago
The fact the the authors of the paper rush for innate explanations (hormone levels in the womb...) that they have no expertise to comment on instead of much more obvious behaviors (maybe self-labelled gay and straight people upload different types of pics or take care of themselves differently, on average), is a clear violation of Occam's razor. The "average gay face" is similar to the "average straight face" with glasses on, a better angle, and a couple of pounds less.
- lxw 9y ago
  Exactly. The authors don't seem to have any basis for their explanations, and the title should really be "neural nets more accurate... on dating website images". Still this is significant, because these are the same images a government or business could potentially access for their own ends.
randyrand 9y ago
"Given a single facial image, a classifier could correctly distinguish between gay and heterosexual men in 81% of cases, and in 71% of cases for women" I can guess if someone of gay or straight with 98% accuracy - just always guess they are straight. Tha ratio of gay to straight in the test data set is perhaps the most important part in determining how well the algorithm actually performs. Are we supposed to assume the computer was shown a 50/50 split of gay and hetero people? It appears that way. But please, tell us.
- r_singh 9y ago
  If the test data does not have a 50/50 split (or something around that ratio), the headline is straight up lies. Skewed test data is the most common problem with research, reminds me of this great video by Veritasium (Is most published research wrong?): https://www.youtube.com/watch?v=42QuXLucH3Q https://www.youtube.com/watch?v=42QuXLucH3Q
- cwoac 9y ago
  From the author's notes: "When presented with a pair of participants, one gay and one straight, the algorithm could correctly distinguish between them 91% of the time for men and 83% of the time for women." So yes, 50-50.
techrich 9y ago
They will be using it to detect criminals next.
eboyjr 9y ago
This has been posted multiple times on HN in the past 6 months: - https://news.ycombinator.com/item?id=15198997 https://news.ycombinator.com/item?id=15198997 - https://news.ycombinator.com/item?id=15197287 https://news.ycombinator.com/item?id=15197287 The author of this paper has created a document that addresses: (1) Summary of the findings (2) You must be wrong – this is pseudoscience! (common criticism of this paper) (3) Our response to an irresponsible press release by GLAAD and HRC; or, a much better response by LGBTQ Nation You can find that here: https://docs.google.com/document/d/11oGZ1Ke3wK9E3BtOFfGfUQuuaSMR8AO2WfWH3aVke6U/edit# https://docs.google.com/document/d/11oGZ1Ke3wK9E3BtOFfGfUQuu...

37 points by helloworld 9y ago

Some additional context and opinion on this: https://www.washingtonpost.com/opinions/ai-gaydar-could-compromise-lgbtq-peoples-privacy--and-safety/2018/02/19/172156bc-126d-11e8-9065-e55346f6de81_story.html https://www.washingtonpost.com/opinions/ai-gaydar-could-comp...

abusoufiyan 9y ago

But why does it matter? What could it possibly be used for? I can't think of a use for this which wouldn't be crossing a line / inappropriate / dangerous.

JorgeGT 9y ago
Homosexual relations are illegal in ~70 countries, and punishable by death in ~10 of those, such as Iran, Saudi Arabia, Brunei, Yemen, etc. Governments in these countries could run this software in their databases, rooting out and prosecuting or even executing those identified. So I would say this kind of software merits discussion.
- barry-cotter 9y ago
  The governments in these countries are evil, not stupid. The false positive rate is too high for this to be useful at anything but a really coarse, maybe check this guy out level. All of the countries you name bar Yemen are easily capable of rooting out and destroying their gay communities if they really wanted to. They don’t. What they want is to make sure everyone involved is very discreet. Hypocrisy is the homage vice pats to virtue etc.

Animats 9y ago

The data used is from dating web sites. That's not a good sample source.

im3w1l 9y ago
Maybe not but still impressive that they beat humans, no?
- krick 9y ago
  Well, assuming the data isn't good — no, obviouly. What "beating humans" would even mean in that case? Imagine you have a dataset of dog and squirrel pictures, with "dog" and "squirrel" (or, actually, "elephant" and "shark") labels assigned quasi-randomly. You make humans and NNs to compete in what label you assigned to them. NN beats humans. Now, what the fuck that result even means?
  - bryanrasmussen 9y ago
    yeah but I guess the data isn't bad in that way in that the sexual orientation of people on the site is probably labeled accurately (in fact I would expect there it's more accurate than, you don't want to lie about what you want on the dating service), the data is bad in that it is perhaps not a representative sample of the population as a whole?
    - im3w1l 9y ago
      > is probably labeled accurately > the data is bad in that it is perhaps not a representative sample of the population as a whole? Yeah that's my thinking too
    - erispoe 9y ago
      What do you mean by labelled accurately? The AI only predicts how an individual self-labelled on a fairly public dating service, not how this person feels or behaves in any other way. There are so many headless torsos on Grindr (or any other gay hookup app) because many men don't want to self label as gay when they look for sex with other men. These men could very well be looking for women on Tinder.
      - bryanrasmussen 9y ago

skjerns 9y ago

This is probaly the best article that you need to read after reading another one of those 'detecting sexual orientation with dating profile pictures/prison inmates/etc' papers: https://medium.com/@blaisea/do-algorithms-reveal-sexual-orientation-or-just-expose-our-stereotypes-d998fafdf477 https://medium.com/@blaisea/do-algorithms-reveal-sexual-orie...

erispoe 9y ago

The fact the the authors of the paper rush for innate explanations (hormone levels in the womb...) that they have no expertise to comment on instead of much more obvious behaviors (maybe self-labelled gay and straight people upload different types of pics or take care of themselves differently, on average), is a clear violation of Occam's razor. The "average gay face" is similar to the "average straight face" with glasses on, a better angle, and a couple of pounds less.

lxw 9y ago
Exactly. The authors don't seem to have any basis for their explanations, and the title should really be "neural nets more accurate... on dating website images". Still this is significant, because these are the same images a government or business could potentially access for their own ends.

randyrand 9y ago

"Given a single facial image, a classifier could correctly distinguish between gay and heterosexual men in 81% of cases, and in 71% of cases for women" I can guess if someone of gay or straight with 98% accuracy - just always guess they are straight. Tha ratio of gay to straight in the test data set is perhaps the most important part in determining how well the algorithm actually performs. Are we supposed to assume the computer was shown a 50/50 split of gay and hetero people? It appears that way. But please, tell us.

r_singh 9y ago
If the test data does not have a 50/50 split (or something around that ratio), the headline is straight up lies. Skewed test data is the most common problem with research, reminds me of this great video by Veritasium (Is most published research wrong?): https://www.youtube.com/watch?v=42QuXLucH3Q https://www.youtube.com/watch?v=42QuXLucH3Q
cwoac 9y ago
From the author's notes: "When presented with a pair of participants, one gay and one straight, the algorithm could correctly distinguish between them 91% of the time for men and 83% of the time for women." So yes, 50-50.

techrich 9y ago

They will be using it to detect criminals next.

eboyjr 9y ago

This has been posted multiple times on HN in the past 6 months: - https://news.ycombinator.com/item?id=15198997 https://news.ycombinator.com/item?id=15198997 - https://news.ycombinator.com/item?id=15197287 https://news.ycombinator.com/item?id=15197287 The author of this paper has created a document that addresses: (1) Summary of the findings (2) You must be wrong – this is pseudoscience! (common criticism of this paper) (3) Our response to an irresponsible press release by GLAAD and HRC; or, a much better response by LGBTQ Nation You can find that here: https://docs.google.com/document/d/11oGZ1Ke3wK9E3BtOFfGfUQuuaSMR8AO2WfWH3aVke6U/edit# https://docs.google.com/document/d/11oGZ1Ke3wK9E3BtOFfGfUQuu...