ai and ml
Maintainers estimate that a quarter of incoming pull requests are low-quality AI-generated code, rising to 31% on larger projects
Generative AI is saving open source developers time while simultaneously flooding maintainers with low-quality submissions, according to a survey by the Linux Foundation.
Respondents estimated that a quarter of incoming pull requests—proposed code changes—consisted of low-quality “AI slop.” Open source projects have spent the past year grappling with AI-generated contributions, useful vulnerability discoveries, false positives, and duplicate reports. While Linux kernel creator Linus Torvalds has warmed to the tools, he has remained critical of low-quality submissions.
The foundation argues that projects need clearer policies and better tools to handle the influx.
Almost three-quarters (71 percent) of maintainers believe generative AI has lowered the barriers to contributing to open source, but just over half (53 percent) disagree that the technology has improved community trust. On average, respondents reported that AI cut code-authoring time by 52 percent. However, for highly complex tasks, 21 percent reported taking longer.
Regarding governance, only 35 percent of projects have a formal policy permitting generative AI use, while 32 percent have no policy and no plans for one, leaving expectations unclear across much of the community.
Hilary Carter, SVP of Research at the Linux Foundation, said: “Open source projects need to design for a growing AI-generated contributor base, not simply react to it. That means setting clear expectations for generative AI, putting responsibility for testing and disclosure on contributors, and giving maintainers better tools to manage incoming pull requests.”
Among large projects, the estimated share of incoming pull requests classified as AI slop rises to 31 percent.
The workload extends beyond proposed code changes. The curl project announced this week it will move low and medium severity flaws to public view to protect a security team that is almost overwhelmed by AI-assisted reports.
Project maintainer Daniel Stenberg said: “We are struggling as a project as all key maintainers feel strained, overloaded, and brought to the brink of what we can muster.”
On the need for better tools for maintainers, Carter added: “If we get those fundamentals right, AI can expand participation without overburdening and increasing costs for maintainers.”