• We recently introduced a policy governing large language model (LLM) assisted contributions to EFF’s open-source projects. • At EFF, we strive to produce high quality software tools, rather than simply generating more lines of code in less time. • We now explicitly require that contributors understand the code they submit to us and that comments and documentation be authored by a human. • LLMs excel at producing code that looks mostly human generated, but can often have underlying bugs that can be replicated at scale. • This makes LLM-generated code exhausting to review, especially with smaller, less resourced teams. • LLMs make it easy for well-intentioned people to submit code that may suffer from hallucination, omission, exaggeration, or misrepresentation.

Article Summaries:

  • The Electronic Frontier Foundation (EFF) has announced a new policy for contributions to its open‑source projects that use large language models (LLMs). The rule requires contributors to understand the code they submit and to write all comments and documentation themselves, while allowing LLMs to assist but not to replace human authorship. Contributors must disclose when LLMs are used, so maintainers can focus on reviewing well‑thought‑out submissions rather than refactoring AI‑generated code that may contain hallucinations, omissions or bugs. The policy balances the practical need for human oversight with the growing prevalence of AI tools, and highlights broader concerns about privacy, ethics and the influence of big‑tech practices.

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