Linux Foundation 调查：AI 让编码时间减少 52%，但四分之一 PR 是低质量 AI 垃圾
AI cuts coding time, but it's also filling open source's inbox with crap
Linux Foundation 调查显示，受访者估计约四分之一的入站 pull request 是低质量 AI 垃圾，大型项目中这一比例升至 31%。调查还称 AI 平均让代码编写时间减少 52%，但 21% 的受访者表示高复杂度任务耗时反而更长；71% 的维护者认为 GenAI 降低了贡献门槛，53% 不同意它提升了社区信任。目前仅 35% 的项目有允许使用 GenAI 的正式政策，32% 既无政策也无计划，curl 项目本周宣布将低危和中危漏洞转为公开，以缓解安全团队被 AI 辅助报告淹没的压力。
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ai and ml
AI cuts coding time, but it's also filling open source's inbox with crap
Maintainers reckon a quarter of incoming pull requests are slop, rising to 31% on larger projects
Richard Speed
MICROSOFT ECOSYSTEM REPORTER
Published wed 21 Oct 2026 // 13:43 UTC
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Generative AI is saving open source developers time while giving maintainers more rubbish to sift through, according to a Linux Foundation survey.
Respondents estimated that a quarter of incoming pull requests – proposed code changes – were 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. Linus Torvalds has warmed to the tools, while remaining critical of low-quality submissions. REG AD
The foundation argues that projects need clearer policies and better tools to handle the influx. REG AD
Almost three-quarters (71 percent) of maintainers reckon GenAI has lowered the barriers to contributing to open source, but just over half (53 percent) disagree that the technology has improved community trust. Respondents estimated that AI cut code-authoring time by 52 percent on average. But for highly complex tasks, 21 percent reported taking longer.
Then there is governance. Only 35 percent of projects have a formal policy permitting GenAI 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 GenAI, 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 severity flaws to public view to protect a security team 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 said: "If we get those fundamentals right, AI can expand participation without overburdening and increasing costs for maintainers." ®
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