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I recommend reading more about copyright law. The questions you are raising have been considered carefully for centuries. While the modern US settled compromise

by kixiQu 4y ago

I recommend reading more about copyright law. The questions you are raising have been considered carefully for centuries. While the modern US settled compromises may be repugnant to you as to me, the expertise behind how these things are considered is valuable and constitutes many-years-of-study's worth. Learning about the complicated contours of what is considered legal and what is considered ethical in "artists [looking] at images" – among which there is a lot of distinction – may explain why others here would expect there to be legal and ethical distinctions among how deep learning systems may process and regurgitate their input.

visarga 4y ago
Regurgitation, in a technical sense (yes, it appears in papers) is under 1% and can be filtered out in post processing. It happens when an images is repeated many times in the training set, say, Mona Lisa in 1000 variants. If the outputs were sufficiently different from the most similar training examples would it be exempt from copyright liabilities? On the other extreme, a single copyrighted image in the training set could spoil the whole model, it would be impossible to make sure the training set is 100% clean.
- kixiQu 4y ago
  > If the outputs were sufficiently different from the most similar training examples would it be exempt from copyright liabilities? This is a great kind of question to ask, and can point us to the right areas of non-deep-learning copyright to think about – but not in a way that lends itself to a quick settled answer in a comment section, I suspect. https://law.marquette.edu/facultyblog/tag/fairey-v-ap/ https://law.marquette.edu/facultyblog/tag/fairey-v-ap/ > On the other extreme, a single copyrighted image in the training set could spoil the whole model, it would be impossible to make sure the training set is 100% clean. Where possessing stolen goods is illegal, it takes quite a lot of effort to determine that an e.g. antiquities dealer has met the reasonable standard of inquiry for 100% of their inventory – but that doesn't mean that isn't the legal requirement. That's an area where we know the legal standard, and this is much newer ground, so it very well may be that tech that depends on datasets too big to take responsibility for may not end up being a great foundation for anything with legal liability attached.
  - visarga 4y ago
    It will be a Napster moment all over again, people want to generate images they don't care about copyrights, and the technology is here. There's already a good enough model (Stable Diffusion) released into the open, it can be executed on any desktop computer. This tech is still very new, it will mature in a few years and we'll get used to it.

by kixiQu 4y ago

visarga 4y ago

Regurgitation, in a technical sense (yes, it appears in papers) is under 1% and can be filtered out in post processing. It happens when an images is repeated many times in the training set, say, Mona Lisa in 1000 variants. If the outputs were sufficiently different from the most similar training examples would it be exempt from copyright liabilities? On the other extreme, a single copyrighted image in the training set could spoil the whole model, it would be impossible to make sure the training set is 100% clean.

kixiQu 4y ago
> If the outputs were sufficiently different from the most similar training examples would it be exempt from copyright liabilities? This is a great kind of question to ask, and can point us to the right areas of non-deep-learning copyright to think about – but not in a way that lends itself to a quick settled answer in a comment section, I suspect. https://law.marquette.edu/facultyblog/tag/fairey-v-ap/ https://law.marquette.edu/facultyblog/tag/fairey-v-ap/ > On the other extreme, a single copyrighted image in the training set could spoil the whole model, it would be impossible to make sure the training set is 100% clean. Where possessing stolen goods is illegal, it takes quite a lot of effort to determine that an e.g. antiquities dealer has met the reasonable standard of inquiry for 100% of their inventory – but that doesn't mean that isn't the legal requirement. That's an area where we know the legal standard, and this is much newer ground, so it very well may be that tech that depends on datasets too big to take responsibility for may not end up being a great foundation for anything with legal liability attached.
- visarga 4y ago
  It will be a Napster moment all over again, people want to generate images they don't care about copyrights, and the technology is here. There's already a good enough model (Stable Diffusion) released into the open, it can be executed on any desktop computer. This tech is still very new, it will mature in a few years and we'll get used to it.