doc: Contributor guide for AI-generated PRs (#18237)

## Which issue does this PR close?

<!--
We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes #123` indicates that this PR will close issue #123.
-->

Part of #18095

## Rationale for this change

<!--
Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
your changes and offer better suggestions for fixes.
-->

## What changes are included in this PR?

<!--
There is no need to duplicate the description in the issue here but it
is sometimes worth providing a summary of the individual changes in this
PR.
-->

In the contributor guide documentation, better explain why large
AI-generated PRs without understanding should be rejected. See more in
the original issue discussion.

## Are these changes tested?

<!--
We typically require tests for all PRs in order to:
1. Prevent the code from being accidentally broken by subsequent changes
2. Serve as another way to document the expected behavior of the code

If tests are not included in your PR, please explain why (for example,
are they covered by existing tests)?
-->

## Are there any user-facing changes?

<!--
If there are user-facing changes then we may require documentation to be
updated before approving the PR.
-->

<!--
If there are any breaking changes to public APIs, please add the `api
change` label.
-->

---------

Co-authored-by: Adrian Garcia Badaracco <[email protected]>
Co-authored-by: Alex Huang <[email protected]>
Co-authored-by: Andrew Lamb <[email protected]>

Author: 4 people

docs/source/contributor-guide/index.md

@@ -113,7 +113,7 @@ do take priority over the conventional commit approach, allowing maintainers to
 
 [conventional commits]: https://www.conventionalcommits.org/en/v1.0.0/
 
-# Reviewing Pull Requests
+## Reviewing Pull Requests
 
 Some helpful links:
 
@@ -175,3 +175,27 @@ The good thing about open code and open development is that any issues in one ch
 
 Pull requests will be marked with a `stale` label after 60 days of inactivity and then closed 7 days after that.
 Commenting on the PR will remove the `stale` label.
+
+## AI-Assisted contributions
+
+DataFusion has the following policy for AI-assisted PRs:
+
+- The PR author should **understand the core ideas** behind the implementation **end-to-end**, and be able to justify the design and code during review.
+- **Calls out unknowns and assumptions**. It's okay to not fully understand some bits of AI generated code. You should comment on these cases and point them out to reviewers so that they can use their knowledge of the codebase to clear up any concerns. For example, you might comment "calling this function here seems to work but I'm not familiar with how it works internally, I wonder if there's a race condition if it is called concurrently".
+
+### Why fully AI-generated PRs without understanding are not helpful
+
+Today, AI tools cannot reliably make complex changes to DataFusion on their own, which is why we rely on pull requests and code review.
+
+The purposes of code review are:
+
+1. Finish the intended task.
+2. Share knowledge between authors and reviewers, as a long-term investment in the project. For this reason, even if someone familiar with the codebase can finish a task quickly, we're still happy to help a new contributor work on it even if it takes longer.
+
+An AI dump for an issue doesn’t meet these purposes. Maintainers could finish the task faster by using AI directly, and the submitters gain little knowledge if they act only as a pass through AI proxy without understanding.
+
+Please understand the reviewing capacity is **very limited** for the project, so large PRs which appear to not have the requisite understanding might not get reviewed, and eventually closed or redirected.
+
+### Better ways to contribute than an “AI dump”
+
+It's recommended to write a high-quality issue with a clear problem statement and a minimal, reproducible example. This can make it easier for others to contribute.