Fair use depends on a lot, and just being a small amount doesn’t factor in. It’s the actual use. Small amounts just often fly under the nose of legal teams.
Fair use is a four factor test amount used is a factor but a low amount being used doesn’t strictly mean something is fair use. You could use a single frame of a movie and have it not qualify as fair use.
When a school professor “prompts” you to write an essay and you, the “tool” go consume copyrighted material and plagiarize it in the production of your essay is the infringement made by the professor?
There’s a long history of this and you might find some helpful information in looking at “transformative use” of copyrighted materials. Google Books is a famous case where the technology company won the lawsuit.
The real problem is that LLMs constantly spit out copyrighted material verbatim. That’s not transformative. And it’s a near-impossible problem to solve while maintaining the utility. Because these things aren’t actually AI, they’re just monstrous statistical correlation databases generated from an enormous data set.
Much of the utility from them will become targeted applications where the training comes from public/owned datasets. I don’t think the copyright case is going to end well for these companies…or at least they’re going to have to gradually chisel away parts of their training data, which will have an outsized impact as more and more AI generated material finds its way into the training data sets.
There’s more and more research starting to happen on it, but I’ve seen anywhere from 20% to 60% of responses. Here’s a recent study where they explicitly try to coerce LLMs to break copyright: https://www.patronus.ai/blog/introducing-copyright-catcher
I don’t have the time to grab them right now, but in many of the lawsuits brought forward against companies developing LLMs, their openings contain some statistics gathered on how frequently they infringed by returning copyrighted material.
You do realize that AI is just a marketing term, right? None of these models learn, have intelligence or create truly original work. As a matter of fact, if people don’t continue to create original content, these models would stagnate or enter a feedback loop that would poison themselves with their own erroneous responses.
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If you read an article, then copy parts of that article into a new article, that’s copyright infringement. Same with ais.
Depends on how much is copied, if it’s a small amount it’s fair use.
Fair use depends on a lot, and just being a small amount doesn’t factor in. It’s the actual use. Small amounts just often fly under the nose of legal teams.
Fair use is a four factor test amount used is a factor but a low amount being used doesn’t strictly mean something is fair use. You could use a single frame of a movie and have it not qualify as fair use.
What does this human is going to do with this reading ? Are they going to produce something by using part of this book or this article ?
If yes, that’s copyright infringement.
Because it’s software.
When a school professor “prompts” you to write an essay and you, the “tool” go consume copyrighted material and plagiarize it in the production of your essay is the infringement made by the professor?
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Copilot lists its sources. The problem is half of them are completely made up and if you click on the links they take you to the wrong pages
It definitely does not cite sources and use it’s own words in all cases - especially in visual media generation.
And in the proposed scenario I did write the student plagiarizes the copyrighted material.
So your question is “is plagiarism plagiarism”?
No, that is not the question nor a reasonable interpretation of it.
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There’s a long history of this and you might find some helpful information in looking at “transformative use” of copyrighted materials. Google Books is a famous case where the technology company won the lawsuit.
The real problem is that LLMs constantly spit out copyrighted material verbatim. That’s not transformative. And it’s a near-impossible problem to solve while maintaining the utility. Because these things aren’t actually AI, they’re just monstrous statistical correlation databases generated from an enormous data set.
Much of the utility from them will become targeted applications where the training comes from public/owned datasets. I don’t think the copyright case is going to end well for these companies…or at least they’re going to have to gradually chisel away parts of their training data, which will have an outsized impact as more and more AI generated material finds its way into the training data sets.
How constantly does it spit out copyrighted material? Is there data on that?
There’s more and more research starting to happen on it, but I’ve seen anywhere from 20% to 60% of responses. Here’s a recent study where they explicitly try to coerce LLMs to break copyright: https://www.patronus.ai/blog/introducing-copyright-catcher
I don’t have the time to grab them right now, but in many of the lawsuits brought forward against companies developing LLMs, their openings contain some statistics gathered on how frequently they infringed by returning copyrighted material.
You do realize that AI is just a marketing term, right? None of these models learn, have intelligence or create truly original work. As a matter of fact, if people don’t continue to create original content, these models would stagnate or enter a feedback loop that would poison themselves with their own erroneous responses.
AIs don’t think. They copy with extra steps.