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AI Policy

RIOT’s policy is that contributors can use whatever tools they would like to craft their contributions, but there must be a human in the loop. Contributors must read and review all LLM-generated code and text before they ask other project members to review it. The contributor is always the author and is fully accountable for their contributions. Contributors should be sufficiently confident that the contribution is high enough quality that asking for a review is a good use of scarce maintainer time, and they should be able to answer questions about their work by themselves during review. Contributions that use AI should also be wary of massive text blobs of AI generated documentation given that these tend to massively bloat the size of the contribution and are often not very useful, and thus are likely to be rejected as extractive contributions.

We expect that new contributors will be less confident in their contributions, and our guidance to them is to start with small contributions that they can fully understand to build confidence. We aspire to be a welcoming community that helps new contributors grow their expertise, but learning involves taking small steps, getting feedback, and iterating. Passing maintainer feedback to an LLM doesn’t help anyone grow, and does not sustain our community.

Contributors are expected to be transparent and label contributions that contain substantial amounts of tool-generated content. Our policy on labelling is intended to facilitate reviews, and not to track which parts of RIOT are generated. Contributors should note tool usage in their pull request description, commit message, or wherever authorship is normally indicated for the work. For instance, use a commit message trailer like Assisted-by: <name of code assistant>. This transparency helps the community develop best practices and understand the role of these new tools.

This policy includes, but is not limited to, the following kinds of contributions:

  • Code, usually in the form of a pull request
  • RFCs or design proposals
  • Issues or security vulnerabilities
  • Comments and feedback on pull requests
  • Contributions to other repositories within the RIOT organization

To ensure sufficient self review and understanding of the work, it is strongly recommended that contributors write PR descriptions themselves (if needed, using tools for translation or copy-editing). The description should explain the motivation, implementation approach, expected impact, and any open questions or uncertainties to the same extent as a contribution made without tool assistance.

An important implication of this policy is that it bans agents that take action in our digital spaces without human approval, such as the @claude agent or Copilot agent. Similarly, automated review tools that publish comments without human review are not allowed. However, an opt-in review tool that keeps a human in the loop is acceptable under this policy. As another example, using an LLM to generate documentation, which a contributor manually reviews for correctness, edits, and then posts as a PR, is an approved use of tools under this policy.

AI tools must not be used to fix GitHub issues meant for beginners as indicated by the “Good First Issue” or “Hack’n’ACK Candidate” labels. These issues are generally not urgent, and are intended to be learning opportunities for new contributors to get familiar with the codebase. Whether you are a newcomer or not, fully automating the process of fixing these issues squanders the learning opportunity and doesn’t add much value to the project.

The reason for our “human-in-the-loop” contribution policy is that processing patches, PRs, RFCs, and comments to RIOT is not free — it takes a lot of maintainer time and energy to review those contributions! Sending the unreviewed output of an LLM to open-source project maintainers extracts work from them in the form of design and code review, so we call this kind of contribution an “extractive contribution”.

Our golden rule is that a contribution should be worth more to the project than the time it takes to review it. These ideas are captured by this quote from the book Working in Public by Nadia Eghbal:

“When attention is being appropriated, producers need to weigh the costs and benefits of the transaction. To assess whether the appropriation of attention is net-positive, it’s useful to distinguish between extractive and non-extractive contributions. Extractive contributions are those where the marginal cost of reviewing and merging that contribution is greater than the marginal benefit to the project’s producers. In the case of a code contribution, it might be a pull request that’s too complex or unwieldy to review, given the potential upside.” — Nadia Eghbal

Prior to the advent of LLMs, open-source project maintainers would often review any and all changes sent to the project simply because posting a change for review was a sign of interest from a potential long-term contributor. While new tools enable more development, it shifts effort from the implementor to the reviewer, and our policy exists to ensure that we value and do not squander maintainer time.

Reviewing changes from new contributors is part of growing the next generation of contributors and sustaining the project. We want RIOT to be welcoming and open to aspiring developers who are willing to invest time and effort to learn and grow, because growing our contributor base and recruiting new maintainers helps sustain the project over the long term. Being open to contributions is a big part of how RIOT has grown. We therefore automatically post a greeting comment to pull requests from new contributors and encourage maintainers to spend their time to help new contributors learn.

If a maintainer judges that a contribution doesn’t comply with this policy, they should close the Pull Request with the following response:

This PR doesn't appear to comply with our policy on tool-generated content,
and requires additional justification for why it is valuable enough to the
project for us to review it. Please see our developer policy on
AI-generated contributions: https://doc.riot-os.org/general/ai_policy/
You may reopen the PR after complying with this policy.

The best ways to make changes less extractive and more valuable is to reduce its size or complexity or to increase its usefulness to the community. These factors are impossible to weigh objectively, and our project policy leaves this determination up to the maintainers of the project, i.e. those who are doing the work of sustaining the project.

Artificial intelligence systems raise many questions around copyright that have yet to be answered. Our policy on AI tools is similar to our copyright policy: Contributors are responsible for ensuring that they have the right to contribute code under the terms of our license, typically meaning that either they, their employer, or their collaborators hold the copyright. Using AI tools to regenerate copyrighted material does not remove the copyright, and contributors are responsible for ensuring that such material does not appear in their contributions. Contributions found to violate this policy will be removed just like any other offending contribution.

Our policy was informed by experiences in other communities: