You can't plagiarize by copying a single word you learned. You can't plagiarize by learning ideas or common expressions and reusing them.
If you read copywritten material and then pass it off as your own you are plagiarizing. Words in a dictionary don't come under that, but I'd bet that if you released a new dictionary that was mostly copied from the old one, most people would consider that plagiarism as well.
I completely agree with this; but my understanding about how LLM work is that they don't copy meaningful segments of text from any specific source. Instead, they predict the next block of text, which they'd only do if they've seen that idea/sequence enough times with context to rank the prediction high enough.
I haven't seen any service copy out large block of text enough to make me think it's reasonable to call their output plagiarized.
Meaning, if the LLM I use will only repeat an idea that many someone's have written about, such that it's seen the idea, or parts of that idea many times. Why is that still plagiarism? Or rather, worthy of direct attribution? Or why was I wrong to use the argument about citing a dictionary here?
(I'm aware that a number of people are working on giving memory so AI can quote from pages like wikipedia. But I don't think it's fair to call that "training data")
Very interesting, any chance you've got a citation for this? I'd like have some sort of proof next time I tell someone that they will happily plagiarize from single sources.
Even if it's not copying word for word, if it's not citing its data, it's still plagiarism. Plagiarism includes copying ideas without crediting their source.