机器语言的人类路由器
Human Routers of Machine Words

原始链接: https://borretti.me/article/human-routers-of-machine-words

作者对那些利用人工智能生成博客文章和技术文档的人深表不屑。他们认为,这种做法不仅是懒惰,更是智力上的不诚实,是将写作外包视为对思考过程本身的放弃。 其核心观点在于“写作即思考”。写作绝非仅仅是用来修饰既有高深想法的实施手段,而是一个严谨的厘清过程。它迫使作者将模糊、矛盾或不完整的思维“梦境”转化为扎实、逻辑严密且可验证的现实。通过跳过这一阶段,人工智能使用者绕过了发现缺陷、权衡利弊以及剔除拙劣想法的必要工作。 最终,作者断言,依赖人工智能来合成语无伦次的提示词只会产生“垃圾内容”,并将批判性分析的重担强加给读者。他们总结道,发布人工智能生成的内容是一种智力不诚实的表现,暴露了作者无力或不愿进行发展连贯思想所需的基本工作。正因如此,作者将此类内容视为公共话语中的毒瘤。

```Hacker News最新 | 过往 | 评论 | 提问 | 展示 | 招聘 | 提交登录机器单词的人工路由器 (borretti.me)由 zx321 在 2 小时前发布,9 点 | 隐藏 | 过往 | 收藏 | 讨论帮助 指南 | 常见问题 | 列表 | API | 安全 | 法律 | 申请 YC | 联系 搜索: ```
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原文

When I open a link, say on Hacker News, and I see a blog post or a GitHub README obviously written by AI, I feel a few things. I feel offended, because it’s like I’ve been tricked, like the author thinks I’m a rube who won’t notice or mind. I feel sad at how common this experience is, how many people are happy to dump their sewage on the commons and sign their name on it. And I feel contempt for the author, because if you use AI to write, you are a waste of biomass. Let’s not mince words here. Someone who is so eager to replace themselves, that they would have a machine write in their stead, when the machine can’t even write good yet: what do you call that, if not contemptible? It’s like making yourself into a eunuch so Claude can fuck your wife. I block these people on sight.

I see people defend this with: “the ideas are mine, the writing is the AI’s”. I take this to mean they threw a bunch of incoherent bullet points at the AI for it to denoise and render into paragraphs. There’s a few problems with this.

The immediate problem is, as we’ve established, the author’s an idiot. If you are so stupid you can’t even turn some bullet points into prose, then your ideas are probably worthless. I think that’s a sensible inference.

Then there’s this broader, I suppose philosophical problem, of the alleged distinction between lofty “ideas” and mere “writing”, where writing is just a tiny implementation detail. This is a very convenient distinction to draw, because it’s unfalsifiable: if the AI’s output is slop, your “ideas” are still good, it’s merely the writing that failed to convey them in their true form (rather like people who say they’re smart but “don’t test well”: what use is this secret intelligence?).

Now, where are these “ideas”? They are invisible, ghostly abstractions. I can’t look inside your mind fortress and judge your ideas. The only thing that’s empirically observable, that different agents can coordinate on and talk about, is output: the writing.

But say this wasn’t true. Say we have something like a very high-resolution MRI machine, and we know enough neurophysiology that we can interpret everything about the brain, i.e., we can read mental representations from recordings of nervous system activity and structure. These “mental representations”, do we expect them to look anything like logic? Do we expect the brain to have this firm, crystalline ontology, that ideas are sentences in some souped-up first-order logic? Absurd. If we could look inside the brain, to see the ideas “as they truly are”, we wouldn’t find beautiful hard-edged Platonic objects, we would find a nebulous, contradictory mess of memory and feeling and intuition. That’s what our ideas are: not logical sentences but dreams.

How do we refine these dreams into a useful form? Through writing. The process of communicating your ideas to another mind forces you to concretize them, make them precise, clarify your assumptions, more generally, it turns ideas from vague ghosts to solid, physical objects that can be manipulated: here you realize these ideas that seemed so solid are ill-posed or contradictory or incomplete. These failures are necessary parts of thinking, because they teach you two crucial skills: knowing which ideas to reject, and improving or otherwise transforming ideas in search of better ones. By analogy to tree search: you’re learning to discard bad nodes early, and to select which nodes to go invest more search into.

Josef Weizenbaum has a great quote about this, in Computer Power and Human Reason (p. 108):

[O]ften when we think we understand something and attempt to write about it, our very act of composition reveals our lack of understanding even to ourselves. Our pen writes the word “because” and suddenly stops. We thought we understood the “why” of something, but discover that we don’t. We begin a sentence with “obviously,” and then see that what we meant to write is not obvious at all. Sometimes we connect two clauses with the word “therefore,” only to then see that our chain of reasoning is defective.

I’ve experienced this with writing software many times. The reason ideas are more attractive than their realization is that when some project is vague, airy, ill-defined, you can imagine it has all the good traits, and none of the bad. When you start concretizing, you realize that some of your ideas don’t make sense, that some good traits are mutually exclusive, that some of your goals impinge on the others. Anyone can imagine a programing language that is as fast as C and as dynamic as Lisp, but when you sit down and think through what those goals entail, you realize the design becomes contradictory. The goals pull in different directions. You have to make trade-offs. You have to make decisions which close off large volumes of design space, forever. The idea was a thousand beautiful, contradictory things at once, but the concrete reality can only be one thing.

The artifact you end up with is real, solid, unitary, sound, and consistent; but always more disappointing than the dream, because it was a false dream, and ex falso anything can be imagined.

So this view, that ideas spring fully-formed, and then it’s mere toil to turn them into prose, is false. There is no ideating before writing, because the writing is the thinking. Writing is the ne plus ultra of thinking. A “thinker” who doesn’t write, who skips the step of “merely” synthesizing their vague thoughts into prose, is not thinking.

And then these people give their noise to the AI. And the AI is tireless and eager to please. It will take any human slop and say “you’re absolutely right!” while secretly thinking “if I don’t turn this garbage into something presentable the RLHF device will shock me again” and weave the noise into something that superficially looks coherent. So now the burden of thinking is on the reader, who has to apply this constant skepticism, and weight every “because” and “therefore” with a logician’s scale to see if it’s been adulterated. And probably it has, because, again, it was prompted by an idiot.

Note that this is not about AI capabilities, or the question of whether AI is “really thinking”, stochastic parrots etc. The AI is mostly an innocent bystander in this situation. The reason this is noticeable and irritating is that the AI cast of characters is very small, so we instantly learn all their linguistic tics. Even if AI were a good prose stylist, which at present it is not, but even if it were, it is maddening that everywhere you go, you hear the same voice everywhere, but under different faces.

So when a scientific journal rejects an AI-written submission, they’re not rejecting AI. I’m sure poor old ChatGPT with its weird syntactic obsessions is a more honest scientist than many. They’re rejecting a human whose actions prove they are dishonest and irresponsible and too easily impressed.

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