While large language models (LLMs) offer an undeniable boost and lower the barrier to entry for new contributors to open-source projects, they also introduce challenges for maintainers.
LLMs are flooding repositories with AI-generated content ranging from helpful to severely broken. Furthermore, there is often no clear way to trace how a contribution was generated or whether it might introduce subtle copyright or licensing concerns.
On the other hand, these tools offer an undeniable productivity boost and help with less glamorous but equally critical aspects of open-source maintenance, such as drafting release announcements and performing translations.
This talk aims to initiate a discussion about the social and technical tensions at play.
What constitutes a ‘contribution’ when machines do most of the work?
How can we preserve trust, maintainability and community health in an era of AI-accelerated contributions?
