4 ms·
If I had to guess, the issue around "black people" is that photos are 2D. We don't really understand just how little information is actually in a photo (we add
by mjburgess 6y ago
If I had to guess, the issue around "black people" is that photos are 2D.
We don't really understand just how little information is actually in a photo (we add huge amounts of info in our perception).
My guess is that predictive systems are using contrast as a guide to essentially 3D structures which, simply, just cannot be reconstructed from 2D. And therefore, probably struggle more on dark faces which have different contrast properties.
- colejohnson66 6y agoWhile contrast is almost certainly part of it, I’d hazard a guess that the training set is also partly to blame. Now, I don’t know much about neural networks (AI), but my understanding is that if you provide a training set representative of the population makeup, (in America at least) it’ll be biased towards white people as it hasn’t “seen” enough black person images. My limited understanding would then make me think one would need equal white person photos as well as black person photos.
- ghaff 6y agoI imagine you're right on both counts. Contrast is certainly an issue. You definitely have to make adjustments to photograph dark skin (or animals with black fur).
- mjburgess 6y agoSure, but were those datasets of 3D snapshots of white people, it wouldnt matter. Black faces and white faces are "statistically equivalent" in 3D. The issue is more, in my view, the hubris of calling this system "facial recognition". It isnt: it's pixel pattern color recognition which sometimes coincides with certain facial patterns.