add LLM and AI tool use policy

content/contributing/index.md

@@ -3,6 +3,9 @@
 Thank you for considering contributing to Pallets! There are many ways to
 contribute to an open source project, see the next section for more ideas.
 
+All contributors and contributions must follow our our
+[Code of Conduct](../code-of-conduct.md) and [LLM and AI Policy](llm-ai.md).
+
 If you would like to ask a question or open an issue or feature request, see
 these guides:
 

content/contributing/llm-ai.md

@@ -0,0 +1,76 @@
+# LLM and AI Policy
+
+Pallets is affected by a large increase in low quality contributions generated
+with LLM (large language model) or "AI" (artificial intelligence) tools. This
+adds to maintainer burden and reduces their available time. Our policy on these
+tools focuses on the human aspect of contribution and growth.
+
+## Summary
+
+* This policy applies to all interactions with our projects and community, not
+  only code and pull requests.
+* We value contributions that are genuinely understood, created, and
+  communicated by humans.
+* If your contribution appears generated by LLM or AI tools, or you attempt to
+  obfuscate that, it will be closed and you are likely to be blocked.
+* Perfection is never required. Your own words and abilities are enough. Do not
+  use LLM tools to translate or "improve" what you say and do.
+* You must carefully consider social, environmental, and quality issues with
+  LLMs before deciding to use them.
+
+## Explanation
+
+This policy applies to all interactions with our projects and community, not
+only code and pull requests. This includes code, documentation, tests, PR
+descriptions, comments, reviews, answers, and all other interactions.
+
+We strongly encourage everyone to participate and contribute without using LLM
+or AI tools. If your contribution looks like it was generated by such tools, or
+you attempt to obfuscate that, it will be closed and you are likely to be
+blocked.
+
+This policy focuses on trust and quality, but there are numerous other
+issues with the social, ethical, resource, and environmental impacts of LLM
+development and use. Deciding to use LLM tools associates you to some degree
+with all these issues, and is a personal moral decision you must carefully
+consider first.
+
+The open source participation model is based on trust. Maintainers build trust
+in new contributors over time as they recognize good contributions from them;
+contributors build trust in projects based on the activity they observe as well.
+Maintainers lose trust in a contributor when they recognize common patterns of
+low quality participation or continued low quality contributions.
+
+When you choose to use an LLM tool to generate output, you look like every other
+person who did so, rather than a unique contributor. Therefore, you inherit the
+distrust maintainers have based on every prior low quality interaction that
+looked exactly like yours.
+
+You may feel pressured to use these tools for many reasons. LLM output
+looks professional and believable by design. It can be hard as an individual to
+see issues with what it generates. As maintainers who see this constantly, the
+context we have is very different, and it becomes much easier to spot. At scale,
+even though any one LLM-generated contribution may be correct, we do not have
+the time or energy to distinguish it from the 10 incorrect ones that look just
+like it.
+
+If you are a new contributor, do not use LLM or AI tools to contribute at all;
+you do not have the trust or experience to take responsibility for what is
+generated. If you are someone who is familiar to the maintainers, and know that
+they already trust you to make high quality contributions, your contribution
+must still genuinely be understood and created personally by you, regardless of
+what tools you may use to assist you.
+
+Your own abilities are enough. From more than a decade of experience, we know
+that everyone is capable of taking an issue, debugging it, and coming up with a
+fix. It's ok if that process requires you to ask us questions. It is ok if that
+process takes time; work on your schedule. It is ok if we have significant
+review feedback. It is ok if we decide to close an issue or PR after you work on
+it, that's not a negative outcome. High quality does not require perfection.
+
+Your own words are enough. It is ok if your writing has typos and does not have
+perfect spelling and grammar. It is ok if English is not your primary language;
+use a traditional translation tool if needed. We are used to reading all that,
+and value hearing from you as directly as possible. Putting your words through
+an LLM tool for translation or "improvement" will produce output you didn't
+intend and will be unable to review.

content/contributing/pr.md

@@ -14,13 +14,14 @@ set up your development environment and run tests. This guide assumes you've
 done that and used the GitHub CLI to fork and clone the repository and add the
 upstream remote.
 
-## AI-Generated Contributions
+## LLM-Generated Contributions
 
-AI-generated PRs and issues are closed on sight, without review or discussion.
-This applies regardless of code quality or correctness.
+Using LLM or AI tools to generate PRs is not allowed. They are closed on sight,
+without review or discussion. This applies regardless of code quality or
+correctness. See our [LLM and AI Policy](llm-ai.md).
 
-AI-generated contributions must not be revived, cleaned up, or used as a base
-for further work. Starting a new PR "on top of" a closed AI submission counts
+LLM-generated contributions must not be revived, cleaned up, or used as a base
+for further work. Starting a new PR "on top of" a closed LLM submission counts
 as laundering and will be treated the same way.
 
 ## Create a Branch