Re: [MAINTAINERS SUMMIT] The role of AI and LLMs in the kernel process

[James Bottomley <James.Bottomley@HansenPartnership.com>]

On Sun, 2025-12-07 at 22:15 -0500, Steven Rostedt wrote:
> On Sun, 07 Dec 2025 18:59:19 -0700
> Jonathan Corbet <corbet@lwn.net> wrote:
> 
> > > I contend there is a huge difference between *code* and
> > > descriptions/documentation/...
> 
> > 
> > As you might imagine, I'm not fully on board with that.  Code is
> > assumed plagiarized, but text is not?  Subtly wrong documentation
> > is OK?
> > 
> > I think our documentation requires just as much care as our code
> > does.
> 
> I assumed what hpa was mentioning about documentation, may be either
> translation of original text of the submitter, or AI looking at the
> code that was created and created a change log. In either case, the
> text was generated from the input of the author

I think this is precisely the problem Jon was referring to: you're
saying that if AI generates *text* based on input prompts it's not a
copyright problem, but if AI generates *code* based on input prompts,
it is.  As simply a neural net operational issue *both* input to output
sets are generated in the same way by the AI process and would have the
same legal probability of being copyright problems.  i.e. if the first
likely isn't a copyright problem, the second likely isn't as well (and
vice versa).

> . Where as AI generated code likely comes from somebody else's code.
> Perhaps AI was trained on somebody else's text, but the output will
> likely not be a derivative of it as the input is still original.

That's an incorrect statement: if the output is a derivative of the
training (which is a big if given the current state of the legal
landscape) and the training set was copyrighted, then even a translated
text using that training data will pick up the copyright violation
regardless of input prompting.

Regards,

James