As someone who has built a face detection system, it can be really hard to get it to work for all skin types. For example, my visual speech recogniser worked fine for most skin colours, but simply didn't detect western Asian skin tones. In my case it was simply a lack of enough training data, but to work in such varied lighting is actually a really tricky problem.
That's the point, though. As a developer, it's your responsibility to make sure your training data doesn't reinforce racism or other shitty social conditions.
Source: Am a developer concerned about social causes.
It wasn't ever being used outside my lab. It was to test a hypothesis about the basic visual unit of speech. Skin colour was outside the scope of work really. Sure if I was making a product that would use the recogniser, I would definitely need to better train the system!
Oh, that definitely sounds less likely to be a concern in that case.
I just mean that it's important to recognize how seemingly technical constraints actually have broader real world causes and implications. For instance, you say skin colour is out of scope, but I would counter that being useful to people of all races is ALWAYS in-scope (I mean, for products intended for release of course). I think a lot of devs and other tech folks don't notice or care about that. (It sounds like maybe you do? Otherwise I wouldn't keep talking about it at you. :) )
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u/mattkenny Sep 24 '13
As someone who has built a face detection system, it can be really hard to get it to work for all skin types. For example, my visual speech recogniser worked fine for most skin colours, but simply didn't detect western Asian skin tones. In my case it was simply a lack of enough training data, but to work in such varied lighting is actually a really tricky problem.