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-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.
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-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.