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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

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!"?

onion2k 7y ago
I was talking about testing the application rather than training the model. You can train a ML model on a diverse range of faces, but if, for example, an application that uses the model doesn't calibrate the camera properly it still won't work for darker faces.
- ALittleLight 7y ago
  I don't understand. The different accuracy of facial recognition by demographic group is common across multiple facial recognition systems. It's highly unlikely that all of the affected systems owe their inaccuracy to a post-training configuration issue. To me it seems more like you are arguing for the sake of arguing rather than that you actually believe in your point. You are just trying to conceive of imaginative possibilities that preserve the "dumb facial recognition developers forgot non-white people exist" interpretation. The problem is that your imagined possible alternatives are not plausible explanations.
  - onion2k 7y ago
    I gave a single example of why an app might fail at facial recognition in some cases. Obviously I wasn't suggesting that would be the case for every app that doesn't work. Suggesting I was is a strawman of ridiculous proportions. I also didn't say anything about ML training data in the post you replied to. My point was about facial recognition app developers not testing with a diverse range of inputs, which is why we see apps failing in public when people try to use them with inputs the app hasn't been tested against. If the apps were well tested those cases would have been caught before the public ever saw them. My original point stands - if your testing sucks then it's very likely that your app will suck too. There will be problems with it that you don't know about, and the users will find them very quickly.
    - thu2111 7y ago
      Do you have any data showing facial recognition doesn't work well on black people? My understanding is that this is an urban legend - it's not true, the algorithms work fine assuming a decent quality camera and video (same for everyone).

onion2k 7y ago

I was talking about testing the application rather than training the model. You can train a ML model on a diverse range of faces, but if, for example, an application that uses the model doesn't calibrate the camera properly it still won't work for darker faces.

ALittleLight 7y ago
I don't understand. The different accuracy of facial recognition by demographic group is common across multiple facial recognition systems. It's highly unlikely that all of the affected systems owe their inaccuracy to a post-training configuration issue. To me it seems more like you are arguing for the sake of arguing rather than that you actually believe in your point. You are just trying to conceive of imaginative possibilities that preserve the "dumb facial recognition developers forgot non-white people exist" interpretation. The problem is that your imagined possible alternatives are not plausible explanations.
- onion2k 7y ago
  I gave a single example of why an app might fail at facial recognition in some cases. Obviously I wasn't suggesting that would be the case for every app that doesn't work. Suggesting I was is a strawman of ridiculous proportions. I also didn't say anything about ML training data in the post you replied to. My point was about facial recognition app developers not testing with a diverse range of inputs, which is why we see apps failing in public when people try to use them with inputs the app hasn't been tested against. If the apps were well tested those cases would have been caught before the public ever saw them. My original point stands - if your testing sucks then it's very likely that your app will suck too. There will be problems with it that you don't know about, and the users will find them very quickly.
  - thu2111 7y ago
    Do you have any data showing facial recognition doesn't work well on black people? My understanding is that this is an urban legend - it's not true, the algorithms work fine assuming a decent quality camera and video (same for everyone).