Ellia Lebleu是WikiProject AI Cleanup的创始成员，2023年志工发布，当清理工作开始时，AI写作经常被明显的陈词滥调所背叛。 今天，该项目的志愿者正在开发一些工具来检测更微妙的机器生成内容形式，并辩论AI在世界最广泛使用的百科全书中的作用。
你什么时候意识到维基百科对AI生成的材料有问题？
艾莉亚·勒布卢：2023年12月左右。 其他几位编辑和我正在维基百科的Discord服务器上聊天，我们都看到一些有同样奇特特征的非常奇怪的文章。 他们重复了“立为遗嘱”或“丰富的文化遗产”等词语。 他们有时有结论部分，或称为“为何如此重要？” 这在2023年和2024年初非常典型的ChatGPT，但对于维基百科的文章来说却非常奇怪——并且很容易发现。 然后，我决定，让我们建立一个关于维基百科的官方项目，以便更多的人能够处理这件事。
埃利亚·勒布卢
Ellia Lebleu是WikiProject AI Cleanup的创始成员。 Lebleu正在雷恩大学因里亚中心攻读AI博士学位，这是法国国家数字科学和技术研究所的一部分。
编辑们今天如何发现AI生成的写作？
Lebleu：到2025年，AI写作的征兆越来越微妙，结构也越来越强。 例如，大赦国际喜欢“三者规则”的负面平行主义，以及其他言论结构，这些结构本身不是决定性的，而是随着积累而变得有意义。 我们也超越文章的范围。 如果有人在5分钟内写了5篇文章，每篇文章数千字，那么有理由怀疑AI.
AI问题只是出现在正文中还是也出现在引文中？
Lebleu：假话或误导性引用已成为一大担忧。 有时AI会完全幻觉引文，虽然今天这更罕见，更常见的是，它发现是一个真正的来源，但得到它的内容完全错误。 AI引用的内容实际上并不支持正在写的东西
英文维基百科最近禁止编辑使用LLMs生成文章。 AI生成的内容还有多少？.
Lebleu：我一直与[AI-检测公司]Pangram合作，我从ChatGPT之前的维基百科内容测试了它，没有发现虚假的阳性，因此其结果提供了非常保守的下限。 在2025年末，它将20%的新条款和草案标注为AI生成。 在2026年初，下降到15%或16%。 但我们还不知道这是因为我们最近的政策产生了效果，还是因为模型越来越强大
维基百科使用AI对抗AI吗？.
Lebleu：另一个来自该项目的编辑器制作了AI源验证器，它通过一个页面上的源并检查它们是否匹配声称。 由于它本身是AI模型，所以不能保证它每次都是正确的。 但如果你想要一些能大规模工作并过滤出明显案例的东西，维基媒体基金会也正在开发一个名为Paste Check的工具，它可以标出直接从一些AI聊天机器人上粘贴的文本。
而我们看到Claude有时会说：“我不能写一篇维基百科的文章，如果所有主要AI公司都执行了这种迅速的拒绝，那也不会完全解决问题，因为仍有一些开放量级的模型可以调整以避免限制。 但对于那些使用商业模型
你能知道禁止人工智能写作的规则是否有效吗？
Lebleu：现在还有点早。 我们看到可能的影响，例如迅速拒绝和AI生成的内容明显略有下降。 但是，我们目前还不知道这是因为模型越来越好，还是因为初学者正在学习规则。 绝大多数人工智能生成的内容都是由初学者编辑提交的
如果AI能够写出真正可靠的维基百科文章呢？
勒布卢：这是我们面临的一大问题。 在通过该准则时，出于非常实际的原因：我们被AI内容淹没，我们没有好的工具，但从那时起，它就进入了更哲学的层面。 许多人将维基百科称为“互联网上最后的好地方”。 作为理论上不受AI slop的地方
许多维基百科的沟通现在都以我们是人文百科为中心。 连人工智能公司都觉得有趣拥有一个纯人文文书，供[训练]AI系统使用，可能很有价值。 维基百科依然如此，并且至少在最近的将来仍将如此
但是，阅读和贡献维基百科的人会希望它成为部分的AI生成，如果这使得它更加全面的话？我们可以保留维基百科的人格
维基百科是否考虑过“Google Zero”这个想法
勒布卢：如果一切经过AI搜索，网站的曝光率直跌到零，我们如何曝光维基百科，并显示它可以编辑，人们仍然可以做出贡献？维基百科在[Google]AI Overviews中经常被引用，但用户可能只看到引用维基百科的AI回答。 他们可能没有意识到维基百科是一个活的项目，他们可以编辑和贡献。
维基媒体基金会正在研究一个归属框架，这个框架可以为AI用户提供更多关于文章的信息[被引用]：文章上次编辑时，其内容有多全面，编辑是否标出问题，甚至可能呼吁采取行动。 未来，读者甚至可能通过AI模型来贡献："AI引用维基百科，但似乎有误。 我可以请求编辑并添加我找到的另一个来源吗？”
我可以看到未来维基百科和AI模型之间非常强烈的共生关系。 我看不出维基百科消失，昨天，AI是东西清理。 今天，明天，我们将呼吸空气。
2026年11月的印刷版中
Eliza Strickland是IEEE Spectrum的特写编辑，她协助开发并塑造杂志的长篇故事。 她还监督Spectrum对人工智能和生物医学工程的覆盖。 她拥有哥伦比亚大学新闻学硕士学位。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
Ellia Lebleu is a founding member of the WikiProject AI Cleanup, a volunteer effort launched in 2023 to find and remove AI-generated material from Wikipedia that breaks the website’s guidelines. When the cleanup began, AI writing was often betrayed by conspicuous clichés. Today, the project’s volunteers are developing tools to detect subtler forms of machine-generated content and debating AI’s role in the world’s most widely used encyclopedia.
When did you realize Wikipedia had a problem with AI-generated material?
Ellia Lebleu: It was around December 2023. A few other editors and I were chatting on Wikipedia’s Discord server, and we had all seen very strange articles with the same odd characteristics. They repeated phrases like “stands as a testament” or “rich cultural heritage.” They sometimes had conclusion sections, or sections called “Why is this important?” That was very typical of ChatGPT in 2023 and early 2024 but very odd for Wikipedia articles—and very easy to spot. Then I decided, let’s create an official project on Wikipedia so more people can deal with this.
Ellia Lebleu
Ellia Lebleu is a founding member of the WikiProject AI Cleanup. Lebleu is pursuing a Ph.D. in AI at the Inria Center of the University of Rennes, part of France’s national research institute for digital science and technology.
How do editors spot AI-generated writing today?
Lebleu: By 2025, the signs of AI writing were becoming subtler and more structural. For example, AI loves the “rule of three,” negative parallelisms, and other structures of speech that aren’t conclusive by themselves but become meaningful as they accumulate. We also look beyond the article. If someone writes five articles of thousands of words each in 5 minutes, there is reason to suspect AI.
Does the AI problem just appear in the main text, or also in citations?
Lebleu: Fake or misleading citations have become a major worry. Sometimes an AI hallucinates a citation entirely, although that’s much rarer today because of retrieval-augmented generation that allows the AI to find sources. More often, it finds a real source but gets its content completely wrong. AI citations that don’t actually support what is being written are extremely commonplace.
English Wikipedia recently prohibited editors from using LLMs to generate articles. How much AI-generated content is still getting through?
Lebleu: I’ve been working with [AI-detection company] Pangram to estimate the proportion of AI-generated content. I tested it on Wikipedia content from before ChatGPT and found no false positives, so its results provide a very conservative lower bound. In late 2025, it flagged perhaps 20 percent of new articles and drafts as AI-generated. In early 2026, that went down to 15 or 16 percent. But we don’t yet know whether that’s because our recent policies have had an effect or because models are getting more powerful and Pangram hasn’t had time to adapt.
Is Wikipedia using AI to combat AI?
Lebleu: Another editor from the project has made an AI source verifier, which goes through the sources on a page and checks whether they match the claims. Since it is itself an AI model, there is no guarantee that it will be correct every time. But if you want something that works at scale and filters out obvious cases, it’s a good first step. The Wikimedia Foundation is also working on a tool called Paste Check, which can flag text pasted directly from some AI chatbots.
And we’ve seen Claude sometimes say, “I can’t write a Wikipedia article; it would go against Wikipedia’s policies.” If all major AI companies implemented that kind of prompt refusal, it wouldn’t solve the problem entirely, because there are still open-weight models that can be tweaked to avoid restrictions. But it would help with people who use commercial models and aren’t especially familiar with the technology.
Can you tell if the rule prohibiting AI writing is working?
Lebleu: It’s still a little early to tell. We see possible effects, such as prompt refusal and the apparent slight drop in AI-generated content. But again, we don’t yet know if that is because models are getting better or because beginners are learning the rules. The vast majority of AI-generated content is submitted by beginner editors, so we’ve made many efforts to make the rule very visible in welcome messages, editing help, and advice.
What if AI becomes capable of writing truly reliable Wikipedia articles?
Lebleu: That’s one of the big questions we’re facing. When the guideline was passed, it was for very practical reasons: We were flooded with AI content, we didn’t have good tools, and we needed to put a stop to it. But since then, it has taken on a more philosophical dimension. Many people have called Wikipedia “the last good place on the internet.” Being a place that was, in theory, free from AI slop has become part of Wikipedia’s identity.
A lot of Wikipedia’s communication is now centered on the idea that we’re a human-written encyclopedia. Even AI companies find that interesting. It can be valuable to have a purely human-written corpus on which to [train] AI systems. The fact that Wikipedia is still that, and will remain that for at least the near future, makes it a precious resource that isn’t replicated anywhere else.
But will the people who read and contribute to Wikipedia want it to become partially AI-generated if that makes it more comprehensive? We could preserve Wikipedia’s identity as a human-written corpus while also offering an AI-assisted option.
Has Wikipedia reckoned with the idea of “Google Zero”—a possible future in which websites no longer get traffic from Google search?
Lebleu: If everything goes through AI search and websites plummet to zero visibility, how do we expose Wikipedia and show that it can be edited and that people can still contribute? Wikipedia is frequently cited in [Google’s] AI Overviews, but users may only see an AI answer citing Wikipedia. They may not realize that Wikipedia is a living project they can edit and contribute to.
The Wikimedia Foundation is working on an attribution framework that could give AI users more information about the article [being cited]: when it was last edited, how comprehensive it is, whether editors have flagged problems, and perhaps even a call to action. In the future, readers might even contribute through AI models: “The AI cited Wikipedia, but there seems to be an error. Can I make an edit request and add this other source I found?”
I can see a very strong symbiotic relationship between Wikipedia and AI models in the future. I don’t see Wikipedia disappearing, but I can see it taking a very different shape. Yesterday, AI was something to clean up. Today, it’s a tool to help us with the cleanup. Tomorrow, it will be the air we breathe.
A condensed version of this article appears in the November 2026 print issue as “Ellia Lebleu.”
Eliza Strickland is IEEE Spectrum's features editor, where she helps develop and shape the magazine’s longform stories. She also oversees Spectrum's coverage of artificial intelligence and biomedical engineering. She holds a master’s degree in journalism from Columbia University.
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