- cross-posted to:
- technology@lemmit.online
- cross-posted to:
- technology@lemmit.online
Thousands of authors demand payment from AI companies for use of copyrighted works::Thousands of published authors are requesting payment from tech companies for the use of their copyrighted works in training artificial intelligence tools, marking the latest intellectual property critique to target AI development.
This describes all art. Nothing is created in a vacuum.
No, it really doesn’t, nor does it function like human cognition. Take this example:
I, personally, to decide that I wanted to make a sci-fi show. I don’t want to come up with ideas so, I want to try to do something that works. I take the scripts of every Star Trek: The Search for Spock, Alien, and Earth Girls Are Easy and feed them into a database, seperating words into individual data entries with some grammatical classification. Then, using this database, I generate a script, averaging the length of the films, with every word based upon its occurrence in the films or randomized, if it’s a tie. I go straight into production with “Star Alien: The Girls Are Spock”. I am immediately sued by Disney, Lionsgate, and Paramount for trademark and copyright infringement, even though I basically just used a small LLM.
You are right that nothing is created in a vacuum. However, plagiarism is still plagiarism, even if it is using a technically sophisticated LLM plagiarism engine.
ChatGPT doesn’t have direct access to the material it’s trained on. Go ask it to quote a book to you.
That really doesn’t make an appreciable difference. It doesn’t need direct access to source data, if it’s already been transferred into statistical data.
It does rule out “plagiarism”, however, since it means it can’t pull directly from any training material.
I should have asked earlier: what do you think plagiarism is?
It really doesn’t. The data is just tokenized and encoded into the model (with additional metadata).
If I take the following:
Three blind mice, three blind mice See how they run, see how they run
And encode it based upon frequency:
1:{"word": "three", "qty": 2}2:{"word": "blind", "qty": 2}3:{"word": "mice", "qty": 2}4:{"word": "see", "qty": 2}5:{"word": "how", "qty": 2}6:{"word": "they", "qty": 2}7:{"word": "run", "qty": 2}The original data is still present, just not in its original form. If I were then to use the data to generate a rhyme and claim authorship, I would both be lying and committing plagiarism, which is the act of attempting to pass someone else’s work off as your own.
Out of curiosity, do you currently or intend to make money using LLMs? I ask because I’m wondering if this is an example of Upton Sinclair’s statement “It is difficult to get a man to understand something when his salary depends on his not understanding it.”
That’s not how LLMs work, and no, I have no financial skin in the game. My field is software QA; I can’t nail down whether it would affect me or not, because I could imagine it going either way. I do know that it doesn’t matter-- legislation is not going to stop this-- it’s not even going to do much to slow it down.
What about you? I find that most the hysteria around LLMs comes from people whose jobs are on the line. Does that accurately describe you?
Edit: typos
It is not literally how they work, no. But, an oversimplified approximation. Data is encoded into mathematical functions in neural network nodes but, it is still encoded data in the same way that an MP3 and WAV of a song are both still the song; the neural network is the medium.
Just because the data is stored in a different, possibly more-efficient manner doesn’t mean that it is not there for all intents and purposes (I suppose one could make the argument of it being transformed into metadata but if it is able to reconstruct verbatim, this seems like a fallacy). Nor is it within free use exemptions of most IP laws to use others’ copyrighted, trademarked, or copy-left data to power a commercial product in ways contrary to licensing terms.
As for my job, well, yes, I do have some anxieties in that area but as a software engineer focused in automation, tooling, and security, I suspect that my position is fairly secure. I would hope yours is too, both for youself and overall software quality. Likely there will be more demand for both of our skillsets with the CRA.
Here: https://www.understandingai.org/p/large-language-models-explained-with
It’s not plagiarism by any definition of the word that makes sense; while the analogy may not be literal, it is perfectly analogous to suggest that learning new words from a Harry Potter book means that any book you write going forward is plagiarizing JK Rowling; the training data helps map the words in the model-- it’s never used as a blueprint when predicting what word comes next in any given scenario. It’s even farther away from copyright infringement-- there is no limited right granted that allows a IP holder to say how that IP can be processed. That’s just not a thing. You’d have just as much leg to stand on if you suggested that Stephen King had the right to prevent people from reading his books in a room with green walls. You can’t just make up new rights. Trademark law is totally insane. I don’t know why you even mention it. It doesn’t even have the same goals as the others.
I am not so sure that this specific role is in any way secure, myself. You may come to the same conclusion after reading that link I provided-- pay attention to how rapidly the LLMs are growing in complexity. I do not wish for anyone to lose their financial security, even a stranger like you, but I can’t help but look at the available information and come to that conclusion.