4 ms·

My first thought was about the diversity of faces used in the demo and how ten years ago, computers didn't think black people were humans. https://www.youtube.

My first thought was about the diversity of faces used in the demo and how ten years ago, computers didn't think black people were humans. https://www.youtube.com/watch?v=t4DT3tQqgRM https://www.youtube.com/watch?v=t4DT3tQqgRM But after that, I was reminded of the paranoia (or not?) around Zoom and that, for an extreme example, the CCP was mining and generating facial fingerprints and social networks using video calls. It seems like this technology is the same concept except put to a useful purpose.

TonyTrapp 6y ago
> ten years ago, computers didn't think black people were humans And they still don't often enough (see recent ExamSoft issues discussed e.g. here: https://news.ycombinator.com/item?id=24641063 https://news.ycombinator.com/item?id=24641063 )
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 ago
  While 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 ago
    I 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 ago
    Sure, 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.

TonyTrapp 6y ago

> ten years ago, computers didn't think black people were humans And they still don't often enough (see recent ExamSoft issues discussed e.g. here: https://news.ycombinator.com/item?id=24641063 https://news.ycombinator.com/item?id=24641063 )

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 ago
While 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 ago
  I 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 ago
  Sure, 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.