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I would say the technology has some issues. For example when you don't include enough black people in your training dataset, probably by simply not thinking abo
by speedgoose 6y ago
I would say the technology has some issues. For example when you don't include enough black people in your training dataset, probably by simply not thinking about it, it can make the algorithm a bit racist. Example : https://twitter.com/Chicken3gg/status/1274314622447820801 https://twitter.com/Chicken3gg/status/1274314622447820801
- naravara 6y agoFunnily enough, this is also true for humans: https://www.nytimes.com/2015/09/20/nyregion/the-science-behind-they-all-look-alike-to-me.html https://www.nytimes.com/2015/09/20/nyregion/the-science-behi...
- scrooched_moose 6y agoThe Oprah one is probably worse: https://twitter.com/Truttle1/status/1274361095285886982 https://twitter.com/Truttle1/status/1274361095285886982
- 1-6 6y agoThanks for the morning laugh.
- cycrutchfield 6y agoI mean, it's amusing, but the face is not aligned the same as the training data so what would you expect?
- GuiA 6y agoAs a computer scientist? Garbage. As a layperson? Magic, because that’s how these things are marketed by startups and journalists.
- tsumnia 6y agoAgreed, while the algorithm is novel, it is vulnerable to introducing false assumptions about the original image. For example, if you were to use this as a method for determine suspects from low quality security camera footage, you may generate suspect images that are biased or completely false.
- 2038AD 6y agoBe careful! Are you sure you want an algorithm to produce more black faces if it would be applicable to policing?
- JulianMorrison 6y agoThis one is very not applicable to policing.
- morelisp 6y agoReally? You don't think the police are interested in depixelating faces?
- JulianMorrison 6y agoI think the police would, if they are doing their jobs (a big "if") be completely uninterested in an algorithm that is the direct equivalent of an unreliable eyewitness confabulating a plausible face for a photofit.
- 2038AD 6y agoIt would be deeply wrong to use such an algorithm to add detail to blurry CCTV images in order to incriminate someone. I don't think every police force, security firm, security agency etc will agree with me on this and that concerns me. Police in my country are already using live facial recognition in some areas.
- JulianMorrison 6y agoIt would be deeply useless. It produces plausible wrong answers. Those are the worst kind of wrong answers, because they are red herrings with statistical near certainty, and yet convincing enough to generate bias.
- 2038AD 6y agoI agree and I don't want these incorrect answers to be made more plausible
- jeffbee 6y agoIt seems like a stretch to call the algorithm "racist". It's the humans with the bias here. It only seems racist because you are capable of recognizing the image on the left and you know he identifies as a black man. The point of the algorithm is that the photo on the right closely resembles, when downsampled, the photo on the left, and the photo on the right is a generative artifact that has characteristics of human faces. It only seems "racist" if you cherry-pick one example and don't look at all the other faces the algorithm generated.
- JulianMorrison 6y agoThe training data is racist. This is a common problem in AI. It produces no black faces. Even as a guess.
- jeffbee 6y agoHow did you conclude this? The paper says 10.1% of the produced face are Black.
- JulianMorrison 6y agoI was mistaken, and going by examples I saw.
- pc86 6y agoCitation needed, because you're making a claim in direct opposition to the paper itself.
- JulianMorrison 6y agoI was mistaken, and going by examples I saw.
- mola 6y agoIt takes one bad application of such technology to ruin a person's life. We can't have a mindless algorithm take or assist decisions that can effect a person's life without extreme caution. Not because people who make these decisions are never wrong but because they are held accountable. These algorithms give false impression of realness and truth while being totally unaccountable. Just look how Yan Lecun (who wasn't even accused of anything) immediately took to throw the blame on the data and not the algorithm. His claim is just a silly demagoguery because with ML there's no real distinction between data and algorithm. But the point is ML is dangerous because it makes it way too easy to pass the buck and doing harm without accountability. Lecunn just made a great demonstration....
- MengerSponge 6y agoA bit. This whole fiasco reminds me of Better Off Ted's "Racial Sensitivity" episode (S01E04).
- Der_Einzige 6y agoSounds like it's time for anti-racist movements to start pressuring the ML community to start introducing and using datasets which aren't biased towards white people. Though, things like black people being more poorly recognized by facial recognition can be a blessing in disguise depending on the circumstances
- leereeves 6y agoSounds dangerous. False recognition can lead police to suspect innocent people, and there are many ways that mere suspicion can lead to a conviction.
- ars 6y agoLet's say the training dataset has the same proportion of black people as their proportion of the population. That, by itself would be biased for the ML, since there are fewer images. But it's not an indication of bias by the people programming it. But this would imply you need huge data-sets for every minority, not matter how small a proportion of the population. It might instead be necessary to teach the model about race as a concept, so it can categorize images, and then process them correctly. But of course that leads to a different can of worms since you are explicitly making a "race aware" ML.
- xigency 6y agoIs it racist though? He has a lighter complexion in that portrait and the result looks like one of his family members: https://twitter.com/iamknighton/status/1274658101006725120 https://twitter.com/iamknighton/status/1274658101006725120
- oh_sigh 6y agoIt's not clear to me why this matters for a research paper. And the algorithm isn't racist - perhaps the training set is. If I want to work on a project like this, and the only appropriate training dataset I have is photographs white males, am I not allowed to work on generating faces until I've fleshed out the data set? It's not like they are offering some service to the general public where they can de-pixelate faces. It's a research paper. A final note: The only professor with her name on the paper(Cynthia Rudin) is very active in researching the intersection of machine learning and social justice. I'm not so sure she would put her name on a paper that can be flippantly described in 3 sentence comments on internet forums as having "some issues" wrt race.