🔶 美国地区法院判决偏向 AI，引发开源开发者担忧
英文标题：🔶 US District Court Decision in AI's Favor Worries Open-Source Developers
美国第九巡回上诉法院在 Doe v. GitHub 案中裁定，AI 生成的新代码若未包含作者署名、版权声明或许可证信息，并不当然构成《数字千年版权法》（DMCA）第 1202 条所称的非法删除或篡改版权管理信息。该裁决为 GitHub、Microsoft 和 OpenAI 带来重要法律胜利，但并未解决使用开源代码训练 AI 是否侵权、是否属于合理使用，以及是否遵守开源许可证等更广泛问题。对开发者而言，以 DMCA 元数据删除为路径追究 AI 代码工具责任的空间有所收窄，但针对实质性复制代码、训练数据复制及许可证义务的诉讼仍可能继续。法院同时指出，若系统像搜索引擎一样返回未附版权管理信息的原始代码，或输出实质性复制受保护作品，案件结果可能不同。
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中文
TL;DR——核心要点
– 第九巡回上诉法院裁定，缺少版权管理信息的 AI 生成代码，并不自动违反 DMCA 第 1202 条。
– 这一裁决为 GitHub、Microsoft 和 OpenAI 带来重大法律胜利，但并未广泛解决以开源代码训练 AI 模型是否构成版权侵权的问题。
– 法院区分了「生成一件未附署名的新作品」与「从现有作品中移除版权信息」两种情形。
在首个针对 AI 编程工具如何使用开源代码的重大上诉裁决中，一家联邦上诉法院给 GitHub、Microsoft 和 OpenAI 带来了一场重要胜利。
众所周知，所有 AI 代码生成程序的学习材料很大程度上来自开源代码。因此，一批匿名开源原告主张，GitHub Copilot 和 OpenAI Codex 是基于 GitHub 公共代码库中的代码构建的，其中包括以开源许可证发布的代码。他们认为，这些 AI 工具生成的代码没有包含原作附带的作者署名、版权声明和许可证条款。如今，第九巡回上诉法院在 Doe v. GitHub 一案中作出有利于 AI 巨头的裁决。
哎呀！
不过，事情或许没有乍看之下那么糟糕。第九巡回上诉法院 9 月 16 日的裁决取决于一个技术性但影响深远的区分：AI 生成代码缺少作者姓名、版权声明和许可证信息，并不必然等同于依据 《数字千年版权法》（DMCA）第 1202 条，从代码中非法移除了这些信息。
代表合议庭撰写意见的 Eric Miller 法官否定了如下观点：工具在新生成作品中未包含版权信息，便自动等同于移除了该信息。法院表示：「创作一件新作品而未包含 CMI（版权管理信息）的人，不能被认为『移除』或『篡改』了任何东西。」法院拒绝如其所言，将「普通的版权侵权主张转化为 DMCA 主张」。
对开源开发者而言，这意味着一条原本可能颇具威力的法律路径已被收窄。对 AI 公司而言，这意味着诉讼风险降低，但这并不意味着它们获得了一张可随意处理开源代码的空白支票。
不过，正如 Open Source Initiative（OSI）新任执行董事 Duane O’Brien 对我所说：「第九巡回上诉法院回答的是关于 DMCA 某一条款的狭窄问题。它并未裁定开发者的开源许可证是否得到遵守，而这一主张仍在地区法院审理。几乎所有开源许可证，从 MIT 到 GPL，都毫不含糊地要求保留版权声明和署名。开发者是在这些条件下向世界提供其作品的；任何基于这些作品进行构建的人，包括开发 AI 工具的公司，都应当遵守这些条件。」
是的，它们确实应该如此。但正如写作者可以证明的那样，AI 公司对受版权保护材料的使用，充其量也可能相当随意。
然而，Software Freedom Conservancy（SFC）律师兼执行董事 Karen Sadler 在一次采访中指出：「人们很容易过度解读这一裁决。」大多数主张——例如 Microsoft 是否在使用代码进行训练前移除了版权信息——都是基于程序性理由被驳回的。原告暗示了这一理论，却没有真正提出该项主张，因此法院没有对此作出裁定，而是认为原告已放弃该主张。或者，如法院所言，「起诉书并非关于训练。它根本不是。」
这并不意味着另一宗论证更充分的案件不会得出不同结论。Sandler 继续表示：「该裁决指出，代码生成确实可能构成侵权。因此，整项裁决的核心在于版权信息是否真的被移除，而不是这种使用本身是否适当。归根结底，本案真正关乎的是这些非常狭窄的主张是如何提出的；在我看来，它并不意味着关于 LLM 使用 FOSS 的任何全面性结论。」
不过，这仍然令人担忧。普遍接受的规则是，代码的开源许可证会随代码一同流转。例如，复用 Apache 许可证文件的开发者应保留相关声明。整合 GPL 许可证代码的开发者，可能需要承担更广泛的互惠义务。即使是 MIT 和 BSD 等宽松许可证，通常也要求保留版权和许可证声明。AI 生成代码切断了这一来源链条。
GitHub 和 Microsoft 从一开始就主张，Copilot 并不会简单复制和粘贴代码。这项裁决并未认可这一立场的每个方面。但它明确表示，仅仅缺少署名，并不会使 AI 代码输出转化为违反 DMCA 的元数据删除行为。
这不仅关系到 Copilot。同样的推理可能适用于 AI 编程助手、通用语言模型和智能体式开发系统的提供商。简言之，适用于所有能够生成代码的 AI 程序。换句话说，对 AI 编程系统而言，仍将照常营业。
不过，法院并未裁定复制开源代码来训练模型是否构成版权侵权。它没有决定此类训练是否属于合理使用；没有确定与受保护源代码高度相似的输出是否侵犯版权；也没有决定当生成代码触发开源许可证义务时，AI 供应商、模型用户，还是双方都可能承担责任。
法院确实认可，通用输出与工具返回一件被剥离信息的现有作品之间存在差别。法院表明，若某个系统的运行方式更像搜索引擎，返回完全相同但未附 CMI 的代码，可能会出现不同的案件。对于输出实质性复制受保护作品的情形，法院也没有排除传统版权主张的可能性。
这是一个重要的限定。AI 编程中的实际风险很可能高度取决于具体事实。常见的循环、排序例程或 API 调用通常不受版权保护；来自特定代码库的大段、独特代码则是另一回事。
这一切意味着什么？请持续关注；未来还会有大量诉讼和法院裁决。不过，开源共同创始人之一 Bruce Perens 对我说：「我们确实正面临这样一个问题：对于专有软件、开源软件以及许多其他产品而言，这实际上意味着版权的终结。最近在向 Richard Stallman 解释此事时，我指出 Copyleft 已成为牺牲品，但他曾经梦想的无版权世界——这正是自由软件背后的真正动机——正在实现，只是伴随着各种未曾预见的情况。」
常见问题
第九巡回上诉法院在 Doe v. GitHub 案中作出了什么裁决？
法院裁定，生成一段未包含版权管理信息的新代码，本身并不构成 DMCA 所规定的非法移除或篡改该信息。
该裁决是否意味着 AI 公司可以自由使用开源代码？
不是。该裁决处理的是一个狭窄的 DMCA 问题，并未解决涉及版权侵权、合理使用或遵守开源许可证的更广泛问题。
法院是否裁定使用受版权保护的代码进行 AI 训练是合法的？
没有。法院没有裁定为 AI 训练复制开源代码是否构成侵权，或是否符合合理使用的条件。
English / 原文
TL;DR — Key Takeaways
– The Ninth Circuit ruled that AI-generated code lacking copyright management information does not automatically violate Section 1202 of the DMCA.
– The decision gives GitHub, Microsoft and OpenAI a significant legal win, but it does not broadly resolve whether training AI models on open-source code infringes copyright.
– The court distinguished between generating a new work without attribution and removing copyright information from an existing work.
A federal appeals court handed GitHub, Microsoft, and OpenAI an important win in the first major appellate ruling over how AI coding tools can use open-source code.
As we all know, all the AI code-generating programs learned their lessons largely from open-source code. So a group of anonymous open-source plaintiffs argued that GitHub Copilot and OpenAI Codex were built using code from public GitHub repositories, including open-source licensed code. They argued the AI tools had generated code without the author attribution, copyright notices, and license terms that came with the original work. Now, the Ninth Circuit has returned a verdict in Doe vs. GitHub siding with Big AI.
Ouch!
But it may not be as troublesome as it first appears. The Ninth Circuit’s September 16 decision turns on a technical but consequential distinction: AI-generated code that lacks author names, copyright notices, and license information is not necessarily the same as code from which that information has been unlawfully removed under Section 1202 of the Digital Millennium Copyright Act (DMCA).
Writing for the court, Judge Eric Miller rejected the idea that a tool’s failure to include copyright information in a newly generated work automatically amounts to removal of that information. “One who creates a new work and fails to include CMI [copyright management information] cannot be said to have ‘removed’ or ‘altered’ anything,” the court said. It declined, in the court’s words, to transform “run-of-the-mill copyright-infringement claims into DMCA claims.”
For open-source developers, that means one potentially potent legal pathway has narrowed. For AI companies, it means reduced litigation risk, but they’re not getting a blank check to do what they want with open-source code.
Still, as Duane O’Brien, the Open Source Initiative (OSI)new executive director, told me, “The Ninth Circuit answered a narrow question about one provision of the DMCA. It did not decide whether the developers’ open source licenses were honored, and that claim is still before the district court. Nearly every open source license, from MIT to the GPL, is unambiguous about the obligation to keep the copyright notice and attribution intact. Developers offered their work to the world on those terms, and anyone who builds on that work, including companies building AI tools, should honor them.”
Yes, yes, they should. But as writers can attest, AI companies can be cavalier, at best, about their use of copyrighted materials.
However, Karen Sadler, attorney and executive director of the Software Freedom Conservancy (SFC), noted in an interview, “It’s very easy to overread this decision.” Most of the claims (like whether Microsoft removed copyright information before using the code for training) were dismissed on procedural grounds. The plaintiffs hinted at the theory but didn’t actually assert it, so the court did not rule on it but instead said that it considered them forfeited. Or, as the court put it, the “complaint is not about training. It just isn’t.”
That’s not to say another, better-argued case, might come to a different decision. Sandler continued, “The decision notes that the generation of code may indeed be infringement. So the whole decision comes back to whether copyright information was actually removed, not about whether the use was appropriate. Ultimately, this case is really about the way these very narrow claims were made, and it doesn’t read to me like any sweeping conclusion about the use of FOSS by LLMs.”
It is worrisome, though. The accepted rule is that code’s open-source licensing travels with it. For example, a developer reusing an Apache-licensed file is expected to preserve relevant notices. A developer incorporating GPL-licensed code can take on broader reciprocal obligations. Even permissive licenses such as MIT and BSD commonly require preservation of copyright and license notices. AI-generated code deletes the provenance chain.
GitHub and Microsoft have argued from the start that Copilot doesn’t simply copy and paste code. The ruling doesn’t endorse every aspect of that position. But it does make clear that lack of attribution, standing alone, will not convert an AI-code output into a DMCA metadata-removal violation.
That matters not only to Copilot. The same reasoning could apply to providers of AI code assistants, general-purpose language models, and agentic development systems. In short, all AI programs that can generate code. Or, in other words, it’s business as usual for AI coding systems.
That said, the court did not decide whether copying open-source code to train a model is copyright infringement. It does not decide whether such training is fair use. It doesn’t determine whether output that closely matches protected source code infringes copyright. And it does not decide whether an AI vendor, a model user, or both may be liable when generated code triggers an open-source license obligation.
The court did recognize the difference between a generic output and a tool returning an existing work with information stripped out. It indicated that a different case could arise if a system operated more like a search engine, returning identical code without accompanying CMI. It also didn’t foreclose conventional copyright claims where output substantially reproduces protected work.
It’s an important caveat. The practical risk in AI coding is likely to be highly fact-dependent. A commonplace loop, sort routine, or API call won’t be copyrightable. A substantial, distinctive code block from a specific repository is a different kettle of fish.
What does all that mean? Stay tuned; there’s a lot of litigation and court decisions to come. Still, as Bruce Perens, one of open-source’s co-founders, told me, “We are indeed facing the issue that this is effectively the end of copyright for both proprietary and Open Source software and many other products. In explaining this to Richard Stallman recently, I noted that Copyleft was a casualty, but the copyright-free world he once dreamed of- the actual motivation behind Free Software- was being achieved, with various unforeseen circumstances.
Frequently Asked Questions
What did the Ninth Circuit decide in Doe v. GitHub?
The court ruled that generating new code without copyright management information does not, by itself, constitute unlawfully removing or altering that information under the DMCA.
Does the ruling mean AI companies can freely use open-source code?
No. The decision addressed a narrow DMCA issue and did not resolve broader questions involving copyright infringement, fair use or compliance with open-source licenses.
Did the court rule that AI training on copyrighted code is legal?
No. The court did not decide whether copying open-source code for AI training constitutes infringement or qualifies as fair use.