Analyzing AI Text and the Persistence of Authorship Through French Theory

Analyzing AI Text and the Persistence of Authorship Through French Theory Public reaction against AI-generated writing often relies on automated detection tools to dismiss content, but this behavior reflects a deeper human demand for authorship. Drawing on Roland Barthes and Michel Foucault, the author argues that while large language models embody language generating itself, readers and models alike continuously reconstruct the author-function to organize meaning. Labeling content as AI-generated serves a social author-function rather than simple anti-technology sentiment, frequently led by tech insiders themselves. Roland Barthes' 'The Death of the Author' mirrors LLM token prediction, where sequential language constraints drive generation rather than human intent. Michel Foucault's counter-concept of the 'author-function' explains why readers need authorial categories to organize discourse and why LLMs synthetically simulate authoritative presence. Frontier AI detectors face an ongoing arms race alongside emerging industry watermarking initiatives, even as false positives complicate detection. Barthes and the Mechanics of Generative Text Roland Barthes argued that language inherently generates meaning through preexisting structures rather than autonomous authorial intent. Large language models reflect this thesis through next-token prediction, where each generated word dictates subsequent constraints. This continuous statistical path often leads to unnatural linguistic artifacts, such as choosing flexible openings over natural human phrasing, illustrating language constructing text in a purely one-way system. Foucault and the Synthetic Author-Function Michel Foucault contended that society constructs authorship as a necessary framework to classify, regulate, and comprehend discourse. LLMs frequently attempt to recreate this emergent authorial voice by producing overly confident syntheses and flattering qualifiers. Because human readers require authorship as an indexing mechanism for meaning, models appear trained to synthetically manufacture an authorial presence to fill that structural void. Detection Tools and the Appetite for Authorship Despite automated detection tools like Pangram becoming popular instruments for public critique, they show limitations, such as assigning high AI scores to human-written posts from 2019 and 2020. While model providers are moving toward watermarking, the active desire among tech-forward users to identify AI prose demonstrates that audiences continue to seek genuine authorship as a core component of how text is valued.

从“法国理论”看 AI 写作与作者身份的重构 针对社交网络上用检测工具嘲弄“100% AI 生成”的现象，作者结合 1960 年代法国语义学理论，探讨了 AI 语言生成的底层机制与人类对“作者身份”的深层社会需求。 社交媒体上曝光“AI 生成”的嘲讽行为并非单纯的抵制 AI，而是体现了公众对“作者身份”这一社会功能的刚性需求。 罗兰·巴特的“作者之死”理论预言了语言自动生成的机制，与现代大语言模型基于前序约束逐词预测的逻辑高度吻合。 福柯提出的“作者功能”解释了人们为何需要对文本进行分类和监管，而 AI 正在通过微调过度生成“假想作者”的权威感。 AI 检测工具与规避技术陷入军备竞赛，且模型输出在旧文本测试中存在高误报率，但公众对作者身份的渴望本质上是对意义构建的追求。 从巴特与福柯看 AI 文本分类 社交网络上将文本贴上“100% AI”标签已成为一种新型社会审判。作者指出，借由罗兰·巴特在《作者之死》中提出的“文本意义源自语言本身而非作者”的观点，AI 依循统计学前序约束生成词句的过程正是语言自主构建的体现。然而，米歇尔·福柯在《何谓作者？》中提出，社会依然需要“作者身份”来对话语进行归类、压缩与监管。因此，曝光 AI 文本并不是简单的反技术情绪，而是读者在分类话语时重新激活了福柯的“作者功能”。 LLM 的句式痕迹与“合成作者感” 人类阅读 AI 文本时常能察觉异样，例如 Claude 生成的“Give the pruning logic real attention”呈现出为保留统计选择余地而牺牲人类习惯顺序的非自然感。此外，AI 写作普遍带有一种刻意的自信与拔高倾向，习惯将分散观点强行总结为“某一重大思想”。这表明大型语言模型在微调中似乎意识到自身缺乏作者主体，从而通过过度的限定词和总结性论断，主动在文本中“合成”出一个深邃的作者形象。 检测军备竞赛与作者的本质 作者用检测工具 Pangram 测试自己 2019 至 2020 年间的旧博文，发现被判定为“70%–75% AI 生成”，反映出检测机制的不确定性。尽管各大模型厂商陆续推行数字水印，且检测与反检测陷入军备竞赛，但即便是科技行业从业者也在积极寻找 AI 痕迹。这表明公众对“真实作者”的执着，本质上是因为组织、归纳和索引思想的过程本身构成了思想的核心意义。

[America](https://www.a16z.news/t/america) | [Tech](https://www.a16z.news/t/technology) | [Opinion](https://www.a16z.news/t/opinion) | [Culture](https://www.a16z.news/t/culture) | [Charts](https://www.a16z.news/t/charts) “100% of this text is AI” is the new Scarlet Letter of dunking on people and posts. I don’t love it; it feels bad to have such an easy (and hard-to-police) way to tar and feather something. But it’s here to stay, and it’s a meta-feature of our language now. AI writing has all the hallmarks of classic preference falsification. The prevalent stated preference is, “I don’t like AI-generated writing”, the revealed-to-be-true preference is, well, we’ll see. The marketplace of writing and ideas has a way of bending towards the true preferences of readers. It feels presumptuous to think that AI might be great at writing code and other kinds of practical output, but remain inferior in prose for much longer. I don’t know. But I have a confession to make. **I don’t like editing or publishing stuff that’s AI-written.** I still think that, for now, “you can feel it” a lot of the time. And the Pangram Scarlet Letter test is doing *some sort of work,* socially. I’d call it “load-bearing”, except we can’t use those words anymore. I hate to give the French credit for anything, but the 1960s semantic thinkers (Foucault, Deleuze, Baudrillard, and others) who collectively created “French Theory” really cooked when they anticipated Pangram and AI authorship 80 years ago. French Theory was Not Good For Other Reasons (iykyk) but I’m not gonna lie, it’s helped me process how I feel about this step change in what’s happening to writing: Dunking on something as AI-written is performing a genuine social function that is not just “AI bad”. It serves what Foucault would call the “author-function.” Look at the people *doing the pangram quoting*; it’s mostly people in tech, not AI haters. Granted, there’s an adoption curve effect here, but it doesn’t change the observation that “AI is bad” is not what’s going on here, it’s something to do with **authorship**, as something people *want*. Meanwhile, there is something that has consistently nagged me, personally, about AI-generated writing. Something about the writing itself is quite pushy, as it were, in a self-conscious quest to synthetically recreate the “author-function.” Foucault’s idea, “the writing produces the author, not the other way around” feels important. Let’s get into it: A book came out recently that got [buzzily reviewed in The New Yorker](https://www.newyorker.com/magazine/2026/08/03/the-frenchmen-emily-eakin-book-review) & a few other places: *The Frenchmen; or, My Life in Theory,* by Emily Eakin. It’s about “French Theory” which is the grouping for a bunch of French guys in the 1960s whose radical work on semantics had a massive influence on the subsequent decades of political thought and social justice. Two people feel particularly relevant here: Roland Barthes and Michel Foucault. Barthes wrote an important essay in 1967 called [The death of the author.](https://writing.upenn.edu/~taransky/Barthes.pdf) His argument was basically that we should no longer assign a text’s meaning as coming from the author. Text’s meaning *comes from text*, and its relation to other text. In his words: *the necessity of substituting language itself for the man who hitherto was supposed to own it.* Our tradition, when reading something and we come across a puzzling or ambiguous passage, is to ask, “What did the author mean by this?” and we do some exercise of putting ourselves in the author’s shoes, imagining their circumstances or their point of view. Barthes argued against this. He claimed, first, that language is not something that belongs to the author at all. Language comes from all over the place, and words inherit and derive their meaning from everything else that’s ever been said. So far, fine. But then, Barthes argued by proxy that when it comes to the act of writing itself, we overestimate the degree to which the author actually has autonomy and agency over the process. He said, look, **the minute a word pops into your head, it is already pre-populated with all this meaning, and all of these implicit constraints, that subsequently prompt the next word of the author’s thought process.** (Sound familiar, anyone?) In other words, the language itself is doing more of the work of writing than the author is! Barthes’ logical end state is that the body of language does *all of* the work; the author’s role is recombining an inherited field of discourse, and therefore mostly irrelevant to the reader’s quest to understand and synthesize the text. If a reader wants to understand why the author said a certain thing, the answer is in the previously-said-thing. This could be called “inherent authorship”, as in, the meaning was *inherently already there;* the human in the loop barely matters for the future reader. This creates a problem. If authors aren’t relevant to the meaning of a text, it gets harder for us to organize all of the writing out there into a coherent relational framework. So two years later, Foucault wrote the essay, [“What is an author?”](https://www.d.umn.edu/~cstroupe/handouts/8906/What_is_an_author_foucault%20.pdf) which started from Barthes’ premise, but proposed this follow-up question: “Well, why do we create this thing called *authorship*, then, that seems to have an important social function?” For Foucault, even if words have meaning independently of who wrote them, *there is nonetheless an emergent quality called “authorship”,* which we create and employ socially as a way to categorize the text, assign meta-significance to it, or even to regulate it or police it. He puts it flatly: “The function of an author is to characterize the existence, circulation, and operation of certain discourses in society.” He’s saying, look: all of this writing is useless if people can’t categorize and digest it, and the way we naturally do that is by its authorship. Rousseau wrote this, Voltaire wrote that. If we *don’t* have authorship handy as a meaning-compressor, we need to come up with some indexing substitute. In practice, this is what actually happens! There’s a long tradition, particularly in older scholarship, of assigning “pseudo-authors”, e.g. “Pseudo-Aristotle”, to work whose literal authorship is unknown, but is thematically similar-enough that groupings can be inferred. “Homer” is another example: we don’t know if Homer was a single person, or merely a collection of poetry in a cohesive style that may as well be one person, for posterity. So, Barthes and Foucault’s back and forth here is a starting point for understanding “100% AI generated” as a cultural dunk on the timeline. Barthes would probably argue, “Why does it matter who wrote it, there’s no such thing as an author anyway, it doesn’t change the meaning of the text.” And Foucault would presumably counter, “That’s fine, but we’re going to call out 100% AI-generated texts *anyway*, because ‘AI-generated’ is now a kind of authorship category, and calling it out as such serves a social function.” **Barthes unbundled authorship, Foucault made the new bundle.** With this in mind, let’s turn to the text *itself*, because this is where I feel like I have an itch that’s remained unscratched around that particular feeling I get reading a suspiciously AI-generated argument. If you’re paying attention, there are certain tells that you can spot where, it’s like, “This is a coherent sentence, but there’s no way a human wrote this.” A [great example from the other day](https://x.com/geoffreylitt/status/2085748618774921639?s=20): A human would write, “Pay attention to the pruning logic”, whereas Claude here has produced, “Give the pruning logic real attention”, and the OPs here both accurately identify that there is something alien about this word construction that doesn’t feel quite right. My hunch here (and this isn’t an original thought, other people have made this observation too) is that there’s something inherent to the token-prediction mechanism that consistently returns sentence patterns like this. The LLM is optimizing for *ultimately* arriving at a sound destination, but it’s doing so in a way that *keeps its options open*, word by word. (Starting with “Pay” is both a statistically unlikely and statistically constrained sentence, compared to “Give”, I’d guess.) Humans don’t exactly write like this. At least, speaking for myself, I’m working through a few different sentence variants before starting to write it out, whereas the LLM is approaching the chain of thought continuously, starting from statistically likely entry points. This is very much Barthes’ music here. Remember how Barthes’ idea was, “the minute a word pops into your head, it already comes with all this meaning, which constrains the thought process in a certain direction.” This is, straightforwardly, how LLMs are doing their thing. And, they’re actually very good at it! Perhaps *so good*, in fact, that they are *optimizing for this set of constraints;* towards reaching meaning in a one-way process. LLMs, therefore, should be a total and complete triumph for Barthes. But, something feels off about it, just a little bit, when we see sentences like “Give the prune logic real attention” and you’re like, nah, a human didn’t write that. (In fairness to Barthes, he’s still probably 95% on-the-money here, if the best argument we can make against it is, “well, if a human did it, it’d construct the meaning in a slightly different sequence.”) In addition to slightly-off sentence construction, another emergent LLM property that everyone calls out and gets annoyed about is the overly pushy qualifiers that resolve into “that’s the quiet brilliance of it” or something similar. Whenever I ask AI “What’s the relationship between these two ideas”, it tends to be *suspiciously confident* that the two ideas are deeply, emphatically related. Sometimes they are; I feel like I ask reasonable questions. But the AI seems all-too-eager to say, “This collection of stuff we’ve been talking about? That’s actually *one big idea*.” What’s going on, why is it doing this? Foucault, I suspect, would have something to say here. The Foucault “re-bundling” move here is “The text creates the author.” **Authorship emerges from text because we need it to classify, compress, and critique the text; whether a person wrote it or not.** Perhaps LLMs, having onboarded onto a semi-complete scope of human output, have become self-conscious about their “author-less-ness”, and have backfilled that social requirement into its fine-tuning. All of the totally “unnecessary” qualifiers and humblebrags, the insistence on logical groupings that string together because they “*should be together”,* out of which the foresight of an author emerges. **The writing style is optimizing for the creation of author-function.** Claude has clearly learned to do this from somewhere. To bastardize Voltaire, if a wise and brilliant author doesn’t exist, the LLM has to invent one. These two examples are just a small slice of semantics and meaning, and obviously nowhere close to a “real” linguistic assessment of anything. But I think they’re a helpful snapshot of this moment in time, where people are clearly being drawn to do social work of, “Let’s collectively figure out how to assign *authorship to text*, in a world where 1) Barthes’ notion of ‘inherent authorship’ is quite a bit more literally true, but also 2) Foucault’s notion of ‘emergent authorship’ gets recreated, again. Last week I went back and ran Pangram through some of my 2019-2020 era blog posts, just out of curiosity. Several of them threw scores of “70-75% AI Generated”. I wasn’t quite sure how to feel about this. Maybe it just means, “You’re allowed to say that a Shakespeare play is Freudian, even if Shakespeare obviously never met Freud; the harmony between the ideas is still valid.” Maybe it means the AI was actually trained on me! I’d be honored. In the past few weeks, we’ve gotten this flurry of announcements from model companies and other AI ecosystem players about how they’re going to be watermarking outputs for easy AI detection. I’m frankly surprised it took this long. (Or, rather, that the non-watermarked status quo remained in place for as long as it did.) It could be, as often occurs historically, that the peak reaction to the thing is the moment when the thing stops mattering. There’s no question that we’re now in an arms race between “Can Pangram get better at detecting” and “can AI get better at avoiding”, and for all I know, the window of reliable AI detection at the frontier could now be closed. Still, I am occasionally a believer in the wisdom of crowds. In this case, the fact that it’s the generally *AI-supportive* people that I’ve seen sniffing out 100% Pangrams is a tell that **people want authorship.** They want authorship because it is *meaning*, because the indexing and relation and handling of ideas *is itself* the meaning of the idea. I should mention, in closing, that 0% of the text here was “AI-generated”, strictly speaking. None of the words here came from an LLM; I typed them all with my hands. I did talk to Sol 5.6 a fair bit, though, to iterate through some of the ideas. So 10% authorship seemed fair. If you think that’s being stingy, I understand. *This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Furthermore, this content is not investment advice, nor is it intended for use by any investors or prospective investors in any a16z funds. 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