Generative AI Policy (was Re: Experimental DSM-based terrain renderer with streamed orthophotos)

Stuart Buchanan <[email protected]> Tue, 2 Jun 2026 14:23:00 +0100
Newsgroups gmane.games.flightgear.devel
Message-ID <CAP3ntyteq4SCYGnQ9UoLFdN-fh=qXoLaZ=J-zNnsMkKji_RtZg@mail.gmail.com>
Hi Florent,

On Tue, Jun 2, 2026 at 1:45 PM Florent Rougon via Flightgear-devel <
[email protected]> wrote:

> Le 02/06/2026, Stuart Buchanan a écrit:
>
> > I don't think we yet have a policy on using AI on the project, but my
> > expectation is
> > that you as the author need to stand behind any contribution.
>
> We have this:
>
>
> https://docs.flightgear.org/contributors-guide/guidelines/generative-AI.html


We do, but we haven't formally adopted that text as a policy.  To save
folks clicking on the link, here's what it says:

----

All contributions to FlightGear must be human authored. Tools such as Large
Language Models, and more generally “AI”, may be used but contributors are
fully accountable for their contributions and responsible for their
quality. They must have reviewed line by line the output of any such tool
and understand the changes they are proposing. So-called “AI slop” and
automatically generated merge requests are unacceptable and will be
rejected out of hand as they waste maintainer time.

----

I think this is a good time to discuss this policy and get consensus from
folks.

The context here is that we should have a policy so that we are consistent
and there are clear expectations for contributors.  We want to strike a
balance between using AI to make volunteer time more effective, against the
risk of AI slop, wasted time and creating an unmaintainable codebase
that no-one understands.

We have a couple of examples which contrast approaches here:

Gerard's work is really impressive, and has been developed with incredible
speed.  As he comments it has only had a limited human code review.
 Should we expect that all code is reviewed by the contributor before being
submitted as a merge request?  We currently have maintainers review all
code going into the repo, which is valuable and regularly picks up bugs.

In contrast, I've been using AI as a tool to assist the development of the
voxel-based clouds, and I'd estimate that it has made my time 4-10x more
efficient in reviewing code, discussing approaches and fixing bugs.  That
said, I've authored all the code and stand by it.  James H has still found
plenty of bugs in it :).

Finally, we've already seen a bit of AI slop on gitlab which simply wastes
volunteer time.

I appreciate that this is a part of a bigger conversation happening within
software engineering as a discipline.  However, we operate within a
slightly different environment here from a commercial software firm:  our
focus is not on delivering value for shareholders, and we are constrained
by volunteer time, with the caveat that we also want to encourage new
contributions.

Best regards,

-Stuart

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