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The author writes: >Machine learning systems are good at identifying cars that are similar to the cars they already know about. They’re also good at identifyin

The author writes: >Machine learning systems are good at identifying cars that are similar to the cars they already know about. They’re also good at identifying faces that are similar to the faces they know about, which is why faces that are white and male are more reliably recognized by these systems — the systems are trained by the people who made them and the people in their circles. But this seems like an absurd claim. Surely it's more likely that darker skin reflects less light than paler skin and so features are harder to detect on darker skin people. This explains why facial recognition works better on white people than on black people. Likewise women are more likely to wear makeup than men are and therefore are more likely to have a visually different face which could cause problems for facial recognition. To assume that dark skinned people aren't involved in creating or testing facial recognition, or that women aren't, seems bizarre and vaguely racist/sexist. It's also a strange and I think poor assumption to think that the different accuracy rates for facial recognition on different demographics are due to a bunch of white dudes being too dumb to train their models on the faces of anyone but themselves. The author also writes about how recommendation systems are "conservative" but to me it actually seems the opposite. Recommendation systems get you to stuff that you haven't tried before. They take what they know about you and progress you to new content or products. For example, I used to listen to listen to a lot of country music on YouTube. Over time my recommendations evolved to include Irish folk music - which I quite like but would've never discovered without YouTube gradually testing and expanding my musical tastes.

di4na 7y ago
Do you have a harder time recognising black or women faces ? If you as human have no more problem, then your argument fail. Or explained otherwise: then don't use techniques that depends on lightning reflection. The fact you use techniques that needs high lightning reflection means that you only care about the result with white faces and/or only tested fitness with white faces.... which is the piece main argument.
- jevgeni 7y ago
  Boy, our eyes sure are racist for using light reflection. Also, obviously the difference between the dynamic range of cameras and our eyes play a major part in technical difficulties in multi-racial facial recognition as well?
- ALittleLight 7y ago
  When I am recognizing a face, that face is attached to a body and in a particular context (e.g. my office, or my home, etc). There are a myriad of different clues, like tone of voice, body language, scent, etc. I am not given a single still image but a video with many frames. Furthermore, the number of people I can recall on sight is probably single digit thousands. All of these are very different for facial recognition software. If I was trying to recognize a huge number of different people, who I had only ever known from still images, and all I had to recognize them were still images then yes, of course, it would be easier to recognize white men than black women for the reasons I just described. I actually don't understand how you can doubt that. Imagine two images of a black woman. In one she has makeup and in the other she doesn't. Do you doubt that these two images are more different, and therefore harder to identify as the same person, than two pictures of a man, neither of which have makeup? Do you genuinely think that the difference in facial recognition accuracy is because models aren't trained on dark skinned or female people? I'm also at a loss as to how you could use any kind of camera or image that didn't depend on the reflection of light.
  - lukeschlather 7y ago
    > I'm also at a loss as to how you could use any kind of camera or image that didn't depend on the reflection of light. You're conflating "high lighting reflection" with "lighting reflection." Lighter faces reflect more light, but if you calibrate your instruments properly you can get just as much information out of a picture with less reflected light.
onion2k 7y ago
To assume that dark skinned people aren't involved in creating or testing facial recognition, or that women aren't, seems bizarre and vaguely racist/sexist. It's unlikely anyone making a facial recognition system would choose to release a version that didn't work, at the very least, for everyone on the team. If the team is only white men then you can see why they might accidently release something that only works on white men's faces. If there was a woman or a PoC on the team they'd have someone saying "Hang on, it doesn't work on me!" The important thing to learn here is that any system is only ever as good as the data used to test it. If your test data sucks then the system you build is also going to suck.
- jevgeni 7y ago
  Also, aren't facial recognition algos trained on broadly available data sets and NOT on the bunch of developers who are working on it? A sample of on average five people seems to be a dumb way to train facial recognition - whether diverse or not.
  - onion2k 7y ago
    Also, aren't facial recognition algos trained on broadly available data sets... They should be, yes, but those training sets can have biases too, and if you use them your app will have the same biases. There are moves to make things like diverse data sets for this exact problem - https://www.theverge.com/2018/6/27/17509400/facial-recognition-bias-ibm-data-training https://www.theverge.com/2018/6/27/17509400/facial-recogniti... A sample of on average five people seems to be a dumb way to train facial recognition - whether diverse or not. I was talking about testing rather than training. You can train your facial recognition model on a diverse range of faces, but if you only test it on a few faces you don't know if it works for diverse people. Teams of developers who test using their own data (eg faces) and nothing else is annoyingly common.
- ALittleLight 7y ago
  This might be a valid theory if facial recognition was a single niche product made by unsophisticated or under resourced developers. That's incredibly far from reality though. There are many well funded groups of serious professionals and academics working on facial recognition with data sets of millions of faces. It's just objectively not correct and not reasonable to think that the reason facial recognition works better on some demographics than others is because nobody thought of training models on those demographics. If you believe that is the case, then do you think people working on facial recognition reading this blog post are slapping themselves on the forehead saying "Of course. Train the models on someone besides the dev team!"?
alicorn 7y ago
Regarding light reflection on facial features and so on, it is worth noting that even _color film_ was already strongly biased towards light-skinned humans [1] Also the argument that the group of people gathering, tagging etc the datasets, feeding them to algorithms and tweaking the algorithms is by definition truly diverse is .. well, have you looked at your average tech campus lately? [1] https://petapixel.com/2015/09/19/heres-a-look-at-how-color-film-was-originally-biased-toward-white-people/ https://petapixel.com/2015/09/19/heres-a-look-at-how-color-f...

di4na 7y ago

Do you have a harder time recognising black or women faces ? If you as human have no more problem, then your argument fail. Or explained otherwise: then don't use techniques that depends on lightning reflection. The fact you use techniques that needs high lightning reflection means that you only care about the result with white faces and/or only tested fitness with white faces.... which is the piece main argument.

jevgeni 7y ago
Boy, our eyes sure are racist for using light reflection. Also, obviously the difference between the dynamic range of cameras and our eyes play a major part in technical difficulties in multi-racial facial recognition as well?
ALittleLight 7y ago
When I am recognizing a face, that face is attached to a body and in a particular context (e.g. my office, or my home, etc). There are a myriad of different clues, like tone of voice, body language, scent, etc. I am not given a single still image but a video with many frames. Furthermore, the number of people I can recall on sight is probably single digit thousands. All of these are very different for facial recognition software. If I was trying to recognize a huge number of different people, who I had only ever known from still images, and all I had to recognize them were still images then yes, of course, it would be easier to recognize white men than black women for the reasons I just described. I actually don't understand how you can doubt that. Imagine two images of a black woman. In one she has makeup and in the other she doesn't. Do you doubt that these two images are more different, and therefore harder to identify as the same person, than two pictures of a man, neither of which have makeup? Do you genuinely think that the difference in facial recognition accuracy is because models aren't trained on dark skinned or female people? I'm also at a loss as to how you could use any kind of camera or image that didn't depend on the reflection of light.
- lukeschlather 7y ago
  > I'm also at a loss as to how you could use any kind of camera or image that didn't depend on the reflection of light. You're conflating "high lighting reflection" with "lighting reflection." Lighter faces reflect more light, but if you calibrate your instruments properly you can get just as much information out of a picture with less reflected light.

onion2k 7y ago

To assume that dark skinned people aren't involved in creating or testing facial recognition, or that women aren't, seems bizarre and vaguely racist/sexist. It's unlikely anyone making a facial recognition system would choose to release a version that didn't work, at the very least, for everyone on the team. If the team is only white men then you can see why they might accidently release something that only works on white men's faces. If there was a woman or a PoC on the team they'd have someone saying "Hang on, it doesn't work on me!" The important thing to learn here is that any system is only ever as good as the data used to test it. If your test data sucks then the system you build is also going to suck.

jevgeni 7y ago
Also, aren't facial recognition algos trained on broadly available data sets and NOT on the bunch of developers who are working on it? A sample of on average five people seems to be a dumb way to train facial recognition - whether diverse or not.
- onion2k 7y ago
  Also, aren't facial recognition algos trained on broadly available data sets... They should be, yes, but those training sets can have biases too, and if you use them your app will have the same biases. There are moves to make things like diverse data sets for this exact problem - https://www.theverge.com/2018/6/27/17509400/facial-recognition-bias-ibm-data-training https://www.theverge.com/2018/6/27/17509400/facial-recogniti... A sample of on average five people seems to be a dumb way to train facial recognition - whether diverse or not. I was talking about testing rather than training. You can train your facial recognition model on a diverse range of faces, but if you only test it on a few faces you don't know if it works for diverse people. Teams of developers who test using their own data (eg faces) and nothing else is annoyingly common.
ALittleLight 7y ago
This might be a valid theory if facial recognition was a single niche product made by unsophisticated or under resourced developers. That's incredibly far from reality though. There are many well funded groups of serious professionals and academics working on facial recognition with data sets of millions of faces. It's just objectively not correct and not reasonable to think that the reason facial recognition works better on some demographics than others is because nobody thought of training models on those demographics. If you believe that is the case, then do you think people working on facial recognition reading this blog post are slapping themselves on the forehead saying "Of course. Train the models on someone besides the dev team!"?

alicorn 7y ago

Regarding light reflection on facial features and so on, it is worth noting that even _color film_ was already strongly biased towards light-skinned humans [1] Also the argument that the group of people gathering, tagging etc the datasets, feeding them to algorithms and tweaking the algorithms is by definition truly diverse is .. well, have you looked at your average tech campus lately? [1] https://petapixel.com/2015/09/19/heres-a-look-at-how-color-film-was-originally-biased-toward-white-people/ https://petapixel.com/2015/09/19/heres-a-look-at-how-color-f...