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AuspiciousApple t1_iuzb7wc wrote

Reply to comment by zacker150 in [D] DALL·E to be made available as API, OpenAI to give users full ownership rights to generated images by TiredOldCrow

It's still a fair question. Suppose I generate something with a common seed (1234, 42, 69420, whatever) and default settings of a popular stable diffusion UI. Other people might conceivably end up generating a very similar image or even the same if they use the exact same prompt.

In that case, does the first people to generate it have the copyright? Do they lose it once it's been generated a second time?

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World177 t1_iuzhhho wrote

Machine learning models of text are generalizations of what the text represents. A generalization being copyrightable seems like a bad idea, though, I don't think the legal system has really decided. In my opinion, owning a generalization is like stating that Apple should own all color gradients because they used them predominately in their advertising. It seems to cover too much, but, Apple probably does own copyright on final created art pieces that use uncopyrightable gradients to create something.

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zacker150 t1_iuzm4z3 wrote

I imagine an image generated using a prompt like "a chicken" would not be copyrightable. However, a prompt like "Asian girl with pink hair playing the piano with two brown pomeranian dog in her lap." would produce a copyrightable image.

The real question is, how long does the prompt need to be to satisfy the minimum human creativity requirement.

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midasp t1_iv0bjwv wrote

The text prompt "chicken" is just the first step. The user still has a mental model of what is considered an acceptable "chicken" and the act of selecting one image that best matches that mental model from a cluster of AI generated "chicken" images should also count for something where creativity and copyrighting is concerned.

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[deleted] t1_iv0eter wrote

[deleted]

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World177 t1_iv3wojd wrote

I don’t think it should be compared to a collage, because that’s not what the model is doing. It’s taking words, and predicting what humans expect to see when given these words describing the image. This is an attempt at generalization, and should start to look similar between models as they improve in quality.

If you take a course on Duolingo, and you learn a language using their copyrighted images, you didn’t steal Duolingo’s content when you applied the knowledge you learned to make creative works for someone in that new language. Though, I think there is some sentiment from people misunderstanding this process and believing that the original owner of the copyrighted content should be entitled to partial ownership too.

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