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For the artist, ImageNet’s problems are inherent to any kind of classification system. If AI learns from humans, the rationale goes, then it will inherent all t
by alfromspace 7y ago
For the artist, ImageNet’s problems are inherent to any kind of classification system. If AI learns from humans, the rationale goes, then it will inherent all the same biases that humans have. Training Humans simply exposes how technology’s air of objectivity is more façade than reality.
An AI being accused of bias tends to really mean it works. Removing bias from AI, I've noticed, requires hardcoded 'fixes' rather than refactoring the algorithms. And in my view, becomes yet another human-curated classification system, and no longer AI.
- munchbunny 7y agoYour point takes a narrow view on correctness and also shows why you need to take the systemic view on the issue. The problem is not that the AI is "inaccurate". The problem is the second order effect: when you build systems on top of this AI's predictions, you cement the input social biases into future systems in a way that is very hard to remediate. The real problem is how to avoid accidentally creating systems that amplify existing social biases. I'm very specifically using the term "social bias" to distinguish from "bias" as a term in ML, because they are very different problems.
- brobinson 7y agoThis comment reminded me of a really interesting article about bias in AI: https://www.chrisstucchio.com/blog/2016/alien_intelligences_and_discriminatory_algorithms.html https://www.chrisstucchio.com/blog/2016/alien_intelligences_...