The Free Software Foundation of Europe recently published an article detailing why it’s legally quite important for developers to disclose and carefully catalog which code was created by LLMs.

https://fsfe.org/news/2026/news-20260825-01.html

Recommendations for AI usage in Free Software contributions

With these issues in mind, the recently published Recommendations When Using LLM-Backed Generative AI Systems for FOSS Contributions by the SFC outlines some of the legal difficulties for copyright and licensing that generative systems have created for software developers who wish to write, maintain, or contribute to Free Software projects.

Notably for the purposes of this article, the SFC recommends the full recording and disclosure of how and when an AI tool was used to assist in the creation of a contribution. As stated by the SFC:

“FOSS project leaders cannot make good decisions about LLM-gen-AI policy if they cannot survey which contributions were assisted, and how much they are assisted. Part of the contribution process should (at least) include a disclosure of what LLM-gen-AI system was used, its version (as these system change over time), and a brief description of how the system assisted the contributor. This information should be included in a machine-readable format in commit logs."

Indeed, such disclosure can be an important foundational step to allow for the accurate assessment of the copyrightability of code that has been assisted or generated by AI tools, in order to assess their licensability into Free Software. Open and clear disclosure is a helpful step for the Free Software community to maintain a healthy licensing ecosystem, which is currently threatened by the legal uncertainties that come with the advent of generative AI.

Additionally, it is worthwhile for developers to document in some capacity the extent of human work that they have done in their software projects, whether it be the writing of code, the selection and arrangement of components within the project, or the extent of human modification of machine generated content.