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I don't agree because it creates this dilemma for creators: you need to put your work out there to get traction, but if you put your work out there and anything public is fair game, then it will be sampled by a computer and instantly recreated at scale. This might even happen without the operator knowing whose work is being ripped off. Commercial art producers have always ripped off minor artists. They would do it by keeping it very similar to the original but just different enough to avoid being sued. Despite this, I personally know two artists who have sued major companies who ripped off their work for ads, and both won million-plus settlements. Why would we embrace this now that a computer can do it and there's a level of deniability? I don't understand how this benefits anyone. |
Generally I don't think people are arguing that copyright law should be more lenient to AI than it is to humans. If your work gets ripped off (a substantially similar copy not covered by fair use) you can sue regardless of tools used in its creation.
Question would be whether machine learning, unlike human learning, should be treated as copyright infringement. There are differences and the law does not inherently need to treat them the same, but it could.
As to why it should: I think there's huge benefit across a large range of industries to web-scale pretraining and foundation models, and I'd like it to remain accessible to open-source groups or smaller companies without huge data moats. Realistically I think the alternative would likely just benefit Getty/Universal with near-identical outcomes for most actual artists.
When the very basis of copyright is for the "progress of sciences and useful arts", it seems backwards to use it in a way that would set back advances in language translation, malware/spam/DDoS filtering, defect detection, voice dictation/transcription, medical image segmentation, etc.