Hank Green found the AI problem that YouTube labels can’t catch

汉克·格林（Hank Green）发现了 YouTube 标签无法捕捉的 AI 问题

YouTube currently requires that content creators let viewers know “when they use AI to meaningfully alter or generate photorealistic content.” The policy draws some strange boundaries. It applies to “AI-generated music” (not photorealistic) but not to “riding a unicorn through a fantastical world” (this could be photorealistic, though it is not plausible). YouTube 目前要求内容创作者在“使用 AI 对照片级真实内容进行重大修改或生成此类内容时”告知观众。这项政策划定了一些奇怪的界限。它适用于“AI 生成的音乐”（并非照片级真实），却不适用于“骑着独角兽穿过奇幻世界”（这可能是照片级真实的，尽管它并不合理）。

YouTube then summarizes the policy in a different way: “Realistic AI content and meaningful changes require disclosure, while non-realistic or minor edits don’t.” But AI uses that require no disclosure can include everything from “idea generation” up through “production assistance, like using generative AI tools to create or improve a video outline, script, thumbnail, title, or infographic.” YouTube 随后以另一种方式总结了该政策：“逼真的 AI 内容和重大修改需要披露，而非逼真或微小的编辑则不需要。”但无需披露的 AI 使用场景涵盖了从“创意生成”到“制作辅助”的方方面面，例如使用生成式 AI 工具来创建或优化视频大纲、脚本、缩略图、标题或信息图表。

Creators are free to clone their own voices for voiceovers. They can also use “AI-generated or altered animation of a missile in a fully animated video.” This results in some odd scenarios. A thrilling 10-second video that shows me riding my AI-generated steed through the horse-killing-fart swamps of Soylentius IV? No disclosure, even though the entire thing is AI-generated. But when I add an AI-crafted lute ballad about the grave dangers I faced in those swamps? Mandatory disclosure. 创作者可以自由克隆自己的声音进行配音。他们也可以在全动画视频中使用“AI 生成或修改的导弹动画”。这导致了一些奇怪的场景。如果我制作了一个 10 秒钟的惊险视频，展示我骑着 AI 生成的坐骑穿过 Soylentius IV 星球上致命的毒气沼泽？即使整个视频都是 AI 生成的，也无需披露。但如果我添加了一首关于我在沼泽中面临的严重危险、由 AI 创作的鲁特琴民谣？则必须披露。

The policy gap becomes more consequential when you imagine a 30-minute video attempting to sway people’s views on geopolitics. AI could generate the premise, do the research, and write the outline. My own AI-cloned voice model could read the AI-drafted script. I could even use AI-generated missile animations. Must I disclose the rampant AI use that drove this entire project? Apparently not. 当你想象一个试图左右人们地缘政治观点的 30 分钟视频时，这种政策漏洞就变得更加严重了。AI 可以生成前提、进行研究并撰写大纲。我自己的 AI 克隆语音模型可以朗读 AI 起草的脚本。我甚至可以使用 AI 生成的导弹动画。我必须披露驱动整个项目的这种泛滥的 AI 使用吗？显然不需要。

But having an AI help in these ways imparts a certain feel and logic to projects, even if the final result is not fully “AI-generated.” Humans approaching topics without AI might find sources through quite different paths, and they might have to read and process more material to get there, giving them a different kind of understanding. They might also note very different things as important, thus creating different outlines of the same material. They might pepper a script with jokes or digressions not usually suggested by an AI. And they might read a script aloud in a more natural way. This doesn’t make the AI wrong, but it does mean that the AI-assisted work will feel different. 但让 AI 以这种方式提供帮助，会给项目带来某种特定的感觉和逻辑，即使最终结果并非完全“由 AI 生成”。人类在不使用 AI 的情况下处理主题时，可能会通过完全不同的路径寻找来源，并且可能需要阅读和处理更多材料才能得出结论，从而获得不同层面的理解。他们也可能注意到完全不同的重点，从而为同一材料创建出不同的大纲。他们可能会在脚本中加入 AI 通常不会建议的笑话或题外话。他们朗读脚本的方式也可能更自然。这并不意味着 AI 是错的，但确实意味着 AI 辅助的作品会给人不同的感觉。

Meet my research assistant

认识一下我的研究助理

I was thinking about this because noted science YouTuber Hank Green recently apologized to fans for his overreliance on AI. Green has made clear that “my words are mine” and that he writes his own scripts. But after fans complained about perceived AI influence on his work, Green looked at his process and concluded they might be right. 我之所以思考这个问题，是因为著名的科学类 YouTuber 汉克·格林（Hank Green）最近因过度依赖 AI 向粉丝道歉。格林明确表示“我的话是我自己的”，并且他亲自撰写脚本。但在粉丝抱怨感觉到他的作品受到 AI 影响后，格林审视了自己的创作过程，并得出结论：他们可能是对的。

“I have been relying too heavily on AI as a research aid,” Green wrote in a Reddit post on July 31. “It can be very useful for this task, giving me access to a lot of papers I didn’t know existed really fast, but I think that has been to the detriment of my work because it has not given me the freedom to find all of my own ways into and around a topic.” “我一直过于依赖 AI 作为研究辅助工具，”格林在 7 月 31 日的一篇 Reddit 帖子中写道。“它在完成这项任务时非常有用，能让我快速获取许多我以前不知道的论文，但我认为这损害了我的工作，因为它没有给我自由去寻找自己探索和理解主题的所有方式。”

The problem, in Green’s case, seems to have been the pressure to produce felt by so many content creators. He used that pressure as a fruitful spur to creation, but he also dealt with it by “using AI to locate papers and other resources for learning about topics.” This quest for efficiency eventually had him moving “so fast that my own process isn’t actually clear to me.” 在格林的案例中，问题似乎在于许多内容创作者所感受到的创作压力。他将这种压力作为创作的动力，但也通过“使用 AI 来定位论文和其他学习资源”来应对压力。这种对效率的追求最终让他“跑得太快，以至于我自己的创作过程实际上变得模糊不清了”。

Green concluded that “making more things does not make me make better things.” And he said that he still needs to come to terms “with the fact that the level of dopamine I’ve been getting from interacting with LLMs… with doing more and more and more and more… is not healthy for me or good for the world.” The result is likely to be fewer videos. 格林总结道：“产出更多内容并不意味着我产出了更好的内容。”他还表示，他仍然需要接受这样一个事实：“我从与大语言模型（LLM）互动中获得的多巴胺水平……通过不断地做更多、更多、更多的事情……对我自己来说是不健康的，对世界也没有好处。”其结果很可能是视频产出量会减少。

Beneath the surface

表面之下

YouTube’s AI disclosure policy and Green’s own wrestling with the technology illuminate different sides of the same question: When does AI support human effort—and when does it replace it in ways that matter? YouTube’s concern is primarily about outright deception. Its policy requires disclosure when a video shows “a real person appear to say or do something they didn’t do” or “realistic scene that didn’t actually occur.” Noting AI use in these cases can be a hedge against the cruder forms of disinformation. YouTube 的 AI 披露政策和格林本人对该技术的挣扎，揭示了同一个问题的不同侧面：AI 何时是在支持人类的努力，而何时又在以重要的方式取代人类？YouTube 的担忧主要在于直接的欺骗。其政策要求在视频展示“真人似乎说了或做了他们没做过的事”或“实际上并未发生的逼真场景”时进行披露。在这些情况下注明 AI 的使用，可以作为抵御粗糙形式虚假信息的一种手段。

But Green’s self-critique is subtler. Far below this “photorealistic” layer of deception, extensive AI use can shape the very basis of creation: ideation, research, and outlining. That is not the same thing as saying that AI use is bad or that its results are inaccurate. It is to say that, even if all AI outputs are correct and well-crafted, they might still possess a style and geometry inherited from the machine now guiding the process. 但格林的自我批评更为微妙。在“照片级真实”的欺骗层面之下，广泛使用 AI 可能会塑造创作的根基：构思、研究和大纲。这并不等同于说使用 AI 是坏事，或者其结果是不准确的。而是说，即使所有 AI 的输出都是正确且精心制作的，它们可能仍然带有从引导这一过程的机器那里继承而来的风格和逻辑结构。

Turning too early—or too easily—to an AI may crowd out offbeat ideas. AI-assisted research may supply answers but not domain mastery. And an AI-generated outline, whether for an essay or a YouTube video, may lock the mind into a predetermined track before it has the chance to wander—and perhaps arrive somewhere more personal. 过早或过于轻易地转向 AI 可能会挤压那些非传统的想法。AI 辅助的研究可以提供答案，但不能提供领域内的精通。而 AI 生成的大纲，无论是用于文章还是 YouTube 视频，都可能在思维有机会漫游——并可能到达更具个人色彩的领域之前——将其锁定在预定的轨道上。