发表机构
UFMG; Univ. Bordeaux, CNRS; Télécom Paris, Institut Polytechnique de Paris（米纳斯吉拉斯联邦大学; 波尔多大学，法国国家科学研究中心; 巴黎电信学院，巴黎理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究分析281项开源项目AI贡献政策，发现83.3%允许AI使用但多附条件，48.8%要求披露，并识别十种对策，揭示政策快速演变，为社区提供基线数据。
AI 中文摘要
开源社区正在汇聚于一种新的治理工件：AI贡献政策。这些政策在几个月前几乎不存在，而现在正被制定并采用。我们分析了281项AI贡献政策，并沿六个维度进行了人工分类；为了研究政策如何变化，我们还随时间追踪了92个专门的AI政策文件。我们回答了四个研究问题，涉及（1）AI使用许可，（2）AI披露实践，（3）AI低质内容对策，以及（4）AI政策演变。我们发现，首先，许可而非例外是常态：83.3%的政策允许或鼓励在代码贡献中使用AI。但许可附带条件，因为67.3%的政策要求高水平的人类参与，43.4%的政策分配了责任。其次，48.8%的政策要求AI披露，最常见的是在拉取请求描述和提交消息中，但必须披露的内容差异很大。第三，我们识别了十种针对AI低质内容的对策，针对拉取请求、用户和自主智能体。最后，政策并非静态：自创建以来，一半的专门AI政策文件已被修订。我们的结果为维护者和研究人员提供了研究AI政策影响的基线和标注语料库。
英文摘要
Open source communities are converging on a new governance artifact: the AI contribution policy. These policies barely existed a few months ago and are now being written and adopted. We analyzed 281 AI contribution policies, and manually classified them along the six dimensions; to study how policies change, we also tracked 92 dedicated AI policy files over time. We answer four research questions on (1) AI usage allowance, (2) AI disclosure practices, (3) AI slop countermeasures, and (4) AI policy evolution. We find that, first, permission is the norm rather than the exception: 83.3% of policies permit or encourage AI in code contributions. But permission comes with conditions, as 67.3% require a high level of human involvement and 43.4% assign accountability. Second, AI disclosure is required by 48.8% of policies, most often in pull request descriptions and commit messages, but what must be disclosed varies widely. Third, we identify ten countermeasures against AI slop, targeting pull requests, users, and autonomous agents. Finally, policies are not static: half of the dedicated AI policy files have already been revised since creation. Our results give maintainers and researchers a baseline and a labeled corpus for studying the impact of AI policies.
CommentsCurrently under review at ACM Transactions on Software Engineering and Methodology (TOSEM)
