Debian developers vote on eight proposals governing AI-generated code contributions

The Debian project is conducting a poll of its developers to decide how to handle contributions produced with large language models. Eight separate proposals have been placed on the ballot, each with its own wording and thresholds for approval. The voting period was extended by one week at the request of the Project Lead.

Proposal A seeks to forbid any LLM-assisted code and would need a 3:1 supermajority to pass, while Proposal C calls for a total ban and Proposal G insists that only human-written code may be submitted directly. At the opposite end, Proposals B, D, E and F would allow AI-generated contributions subject to conditions such as licensing attribution, accountability, disclosure and climate considerations. Proposal H focuses solely on the environmental impact of LLM training as a deal-breaker.

Adopting a restrictive outcome would require contributors to avoid LLMs, potentially increasing manual coding effort and limiting the use of automation tools for routine tasks. Choosing a permissive outcome would impose new workflow steps, including tracking AI use, ensuring compliance with the Debian Free Software Guidelines, and providing clear attribution for generated snippets. Both paths carry administrative overhead for maintainers who must enforce the chosen rule set.

Enforcement may stall if contributors cannot reliably distinguish between locally run and cloud-based LLMs, especially when the environmental impact of training is the primary concern. Disagreements over the exact scope of “practical” use could lead to inconsistent application across packages. Moreover, the reliance on self-reporting and disclosure creates a trust gap that the project may struggle to close.