"So, if we publicly shame people whose text looks like it might have been written by a machine – because it mimics the language used for human reasoning – and people stop writing in ways that they internalize as "AI writing" out of fear of false detection, it sends a signal that your language for reasoning must be policed, or you too could be held up to public scrutiny."
This is honestly both terrifying and well articulated.
Surely it hasn't escaped your notice that the LLMs don't tend to stick to just the one set of idioms/devices. They're constantly running new batches of them into the ground
This is honestly a very, very naive statement. We are social animals and we naturally gravitate towards devaluing and shaming certain styles of speech. We police speech already! It’s often unfortunate, but it’s not devoid of function. I, for one, am happy with shaming LLM speech. It’s never been so easy to detect lazy thinking.
Last week I read through 10 project proposals by students. Two of those ticked all boxes for LLM writing throughout their full text. Not that I checked for LLM-markers specifically, but if a text makes you go: wait a minute, am I reading the output of an LLM? only to then present you with more markers also content-wise, that will have an impact on the human reading the text.
And it should. If someone sends me an obvious copy-paste mass email it also has an impact on how serious I take that email to be meant as an actionable proposal targeted at me specifically.
If they half-ass their proposal which has to do with language I can reasonably infer they may also half-ass the real world implementation which in this case also had to do with language. If you're unable to describe your own idea on half a page of paper in your own words, maybe the students who are able to do so should be treated fair.
I don't care wheter or not they use LLMs, in fact do. But engage with the ideas and results and convince me you really care about them.
It's easy to focus in on particular linguistic tics, which will probably get smoothed away in future training. The underlying issue is that the LLM is trying to ape meaningful writing - which takes the reader from A to a surprising Z - without generally basing it on a meaningful insight.
Most of the common tells stem from that desire to signal the gap between what it's writing about now and how you previously thought things worked. And they really fall flat when it's writing about some milquetoast truism with all the edges sanded off.
Rather than have "Z" be self-evidently interesting, the LLM need to tell us that it's not "A". Except no one thought anything was "A" in the first place, and the "Z" is barely a "B" let alone a "Z".
Or things are "quietly X," implying that there is some secret knowledge that other people have.
Barring that, the LLM will signpost arguments, telling you how interesting things are. "This is the critical part..." before launching into another banal non-observation. Why have only "Section Header" when you can have "Section Header (another idea I had) - omg I just have so much to say about this". Maybe a list of weak ideas, presented in multiple ways. Bulleted with emojis. As a rule of three. As choppy sentences in a paragraph.
All of these follow the same pattern - trying to follow the FORM of having something interesting to say that differs from consensus understanding, without having the intelligence or boldness to actually midwife a new concept into the world.
AI output reads like homepage marketing content (e.g. the text that fades in when you scroll down an apple product page) expanded to fill some context window size (the paragraphs tend to be about the same size).
What you get is vacuous, choppy, wordy, and hyperbolic. I have found that adding secondary passes for tone and style improve the readability dramatically.
If the system prompt is “flesh out template y with thought x” the form drives the generation, it feels compelled to use the whole template.
Of the system prompt is “refine thought x and then format it with the appropriate parts of template y” it becomes a simple transformation and formatting.
A lot of current gen llm pain appears to be being in the early days of understanding the nuance of system prompts.
If you present the idea as "an idea" rather than "my idea", it's pretty good at challenging, solidifying, and refining it. It still leans on the same forms in the writing part, but I think it can be tuned to not insist upon the idea's brilliance so breathlessly.
Yes, this is the kind of thing I've been hoping more people would notice.
I think another tell with a long lifespan is that it will try to write about a thing it experienced, but having no real knowledge of the qualia, it'll end up only referring to it (not uncommonly using "that") and leaving all the substance as an exercise for the reader
I like that these AI idioms exist. They're like watermarks for text. It's worth the cost of humans avoiding them. Companies will eventually train their models to be undetectable, but society would be better if they didn't.
Except that the entire point of the article is that they're not AI idioms. They're not "watermarks for text." They're legitimate language constructions that LLMs tend to overuse, but that real humans also use. Real humans do, in fact, say "align with" all the time, just as often as "corresponds."
And you can pry my em dashes from my cold, dead hands.
Well reading between the lines I don’t think they’re saying all of those uses are AI. They’re legitimate constructs, like the em-dash, en-dash, and hyphen, all of which I used to use regularly. But now they’re AI tells so I use them sparingly.
The article is not God, just because it claims something doesn't mean we have to accept it.
For better or worse (and pretty much for worse), these usages have become AI idioms. Language evolves over time, things that used to be harmless become offensive, certain terms end up taking on the complete opposite meaning than their original meaning, and we are watching certain language patterns and idioms become watermarks for AI and while it sucks, it doesn't make it false.
I'll just quote from the article, which no one claimed was God and that's really a weird way to dismiss it, but you do you:
"We create a culture of self-censorship and AI-detector-pressured rewriting and paraphrasing as people strive to avoid these witch hunts. That is the opposite of protecting human expression. We should resist normalizing a trust in any machine's ability to determine matters of guilt. If using AI to write is, at its worst, an industrialization of the mind, then AI detection, at its worst, becomes a surveillance system for thought."
And, I'm sorry (I'm not), but I am not going to just roll over and shrug and say "welp, guess we all need to dumb our writing down to keep well-meaning idiots from screeching 'AI! AI! AI! WHOOP! WHOOP WHOOP WHOOP!' at us." That isn't the evolution of language. It's Idiocracy.
What's worse is neurodivergent writing, including my own, often resemble AI output. Now it feels like I'm having to alter my own voice in online discussions just to specifically avoid being accused of pasting an AI response.
The "AI Detection" tools employed by schools also regularly flag writing from those with Autism, ADHD, and non-native English speakers as being AI generated as well.
So, naturally, I can't stand the phrase "write like AI" when these things tend to come up because no, there are no humans that "write like AI" it's the models that have stolen the literary devices from us and now have poisoned them.
I agree with the feeling. But if you agree with the analysis of the article, this cat & mouse game ultimately amounts to stop disclosing our reasoning threads through commonly accepted linguistic structures. That's quite a price to pay as a society...
I actually find the "AI idioms" rather less grating than emoji-vomit. That said, I don't know why certain LLM output seems to be full of the latter; certainly no real human writing I've seen has that style, but perhaps it's a result of training on data that probably should've been done without.
Humans are just trying to do what Pangram is trying to do: guess what is AI, badly. The post argues against this:
> In the end, shaming people for writing that gets flagged as AI can lead people to sidestep structures the model has learned from us: structures that are effective tools for argumentation. We take the tools of critical thinking out of the kit at the time we most need them.
This is my position with this stuff. It became part of the LLM loop because it’s used a lot- it’s used a lot because it’s effective.
Now we’re going to stop using effective rhetorical methods because they imply AI, even if we know we’re not using AI?
It reminds me of, as a teenager, asking my dad if he ever saw Led Zeppelin live. He hadn’t, because he didn’t really like fans of Led Zeppelin and didn’t want to be associated with them.
As an ashamed fan of certain bands I get this instinct but I also promised to myself when I heard this that I would do my best to not allow other people to influence how I thought about things I enjoyed.
On the same note I’m trying to be “braver” about things like em-dashes, though my personally style has always been to use them as I did in this comment- like this, which I guess distinguishes me, until an LLM picks that up too…
I like to use a lazy variant -- it's not a double dash, or a weirdly written plus, it's a an em-dash that says "I don't even have this key on my keyboard, are you actually using alt-codes or what am I missing?". Not with a shout or a whisper, but with the quiet courage of just being -- but not an incomplete representation of a whole, but rather the fullness of that very distillation of honest, simple pragmatism. Not less, just different.
I don’t think it’s quite the same though. The way it constructs thoughts is very algorithmic. If you look at the Wikipedia ai text doc it’s a much better explanation and arguments for not immediately blaming someone for using ai.
I don't think so at all. Models are trained in many ways and are changing aggressively, resulting in different patterns in different regions, domains, languages, and will be different 3, 5, 10 years down the line. Having everyone try to learn and adapt around how to stay within very magical, fuzzy, and ever-changing boundaries to avoid appearing to be an AI, instead of focusing on producing good writing or communicating as it is natural to them, seems like a recipe for bad thinking and arbitrary reactions.
Possibly, but it's not a necessity. Click baiting (i.e. yt videos) has evolved to stable standards, that's at least my impression.
Also, products often only get improved until they are "good enough", not until they are "good". It happens, but then they just iterate towards the "how bad can I become" baseline from the other side.
AI companies generally are not in the "let's make the best AI possible" business but in the "let's make the most money" business. This just hasn't fully manifest because they get flooded with VC.
Counterpoint: I think it can also useful to avoid LLM-isms because it's a quick test to check whether you're saying something derivative or actually saying something novel/interesting/significant. Which is to say, if someone could credibly accuse me of being an LLM, then that means my writing is no better (for whatever definition of "better" you want to use) than what happens when you melt down all of human language into a paste and then reconstitute it into featureless little cubes.
Obviously there are exceptions; you can use certain constructions in a way that's still unmistakably human, or use them within a larger context of unmistakably human writing. But in general it makes me think about Orwell's argument against cliches:
> A newly invented metaphor assists thought by evoking a visual image, while on the other hand a metaphor which is technically ‘dead’ (e. g. iron resolution) has in effect reverted to being an ordinary word and can generally be used without loss of vividness. But in between these two classes there is a huge dump of worn-out metaphors which have lost all evocative power and are merely used because they save people the trouble of inventing phrases for themselves.
If LLM-isms give readers the impression that I'm too lazy to phrase things in my own words, even if I did in fact phrase things in my own words, then I take that as a sign that I should pick better words!
Granted, I've had a strong desire to write as distinctly and un-cliche-ish-ly as possible since long before ChatGPT's public launch, so I might not be as grumbly as other commenters who feel like this would force them to change how they write.
i was just yesterday yelling at Gemini for telling me, five times in a row, that it "had found the absolute truth of the problem" when it was wrong all 5 times lol
It's a useful construction. "It's not true love, you matched with her on Hinge last week and have never met her, please don't send her $1000 in Apple gift cards" is punchy.
No, fuck that. I'm not going to think twice about what I write just to avoid an AI checker, and I will delve into em dashes with gusto if that's what the writing calls for.
I'm not sacrificing the language simply to sound less like AI--that's absolutely a losing game.
And if anyone thinks my hand-crafted prose is AI-generated, they're free to look elsewhere. Right now AI detectors peg my pre-AI work as 30% AI-generated, and I'm certain that number will only increase as LLMs improve.
> I'm not going to think twice about what I write just to avoid an AI checker
It depends on your environment, I guess. If you're a student writing an essay or a researcher writing a paper, it's in your best interest to avoid sounding like an LLM, which means going out of your way to avoid certain idioms, even if it means letting go of things you liked to write.
I used to love a spaced en dash (the British English equivalent of the American unspaced em dash), but I wouldn't risk it now.
I remember someone posting about the most human of all traits being reassuring to see: Typos. I'm pretty sure people are not as averse to leaving or finding typos in text as they were 5 years ago, as these days it's a signal of humanity.
Same has been applying to art for a while. Several artists who have an "AI-ish" style have been wrongfully crucified for using AI. And been forced to post videos of their process end to end, in order to prove that they aren't using AI. It's a thing for artists to post their new stuff with: "AI could never do this."
Slightly off topic, I'm not sure, but way back in the day (2000ish) a friend of mine used PERL scripts to scrape all the big databases which existed at the time, namely IMDB.
He used PERL for scraping and the same for generating "new" content with what he had scraped. He made a bunch of static websites with ads. The sites connected to each other. Sports, Celebrities, Movies, you name it. He had a formula.
Those sites were profitable enough that he could travel the world and have fun, basically. His mother collected the cheques from Google and cashed them into his account.
Now to get to the final point here, his secret was simply TYPO INJECTION to avoid Google's then embryotic duplicate content detection.
> There is danger in evaluating for language patterns over its content
I agree, but it’s worth noting that that has been done since long before LLMs. Fifteen years ago, I used to teach a graduate course on academic writing pedagogy. The students and I would read research papers on the teaching of academic writing; we also analyzed textbooks and course syllabuses to get an idea about what was actually being done in classrooms. While phrases like “critical thinking” did come up, the overall focus was clearly on language patterns: sentence and paragraph structure, the use of transition words, vocabulary for hedging and boosting (i.e., making assertions seem weaker or stronger), etc.
In a university context, it can be very difficult to evaluate student writing based on its content. In humanities-focused and creative writing, what the student decides to say can be seen as an extension of the student’s personality, identity, and individual experience; if a teacher evaluates the content, including the reasoning, it can seem that the teacher is evaluating the student as a person. And if the students are in the sciences, especially at the graduate level, the writing teacher often won’t even understand what the students write because it is too technical. Teaching and evaluating language patterns, not content, is often the only option.
In one of the essays posted here, which was, ironically, about AI in education, a sentence, that an AI could not possibly write, that I could possibly write, because of its length and unusual structure, before finally reaching the verb, went on for 25 words.
I don't know if it was written that way to show trust in the reader's intelligence, show disregard for reaching a wide audience, show a demonstration of skill, or was artifact of someone just thinking at that level.
Your first sentence is 45 words and contains 9 commas.
> I don't know if it was written that way to show trust in the reader's intelligence, show disregard for reaching a wide audience, show a demonstration of skill, or was artifact of someone just thinking at that level.
It's fine. People will always find something to be publicly unhappy about.
Example 1. Someone reached out to me on LinkedIn "from HN", when I replied to their initial message they just said "You look like an AI trawler" and disconnected.
Example 2. I read a popular non-English tech blog aggregator which also encourages comments and discussion. Since ~1.5 years ago every other comment is "thank you author, but if I wanted to read AI I would as AI" or some variation thereof.
I think people overestimate the radius of avoidant behavior against AI idioms, and underestimate how the trove of AI generated text actually influence people's writing. It's not a one way street. If you mostly read AI generated content, your writing will inevitably resemble it.
I liked everything in this post, with one exception. I'm less sure that avoiding speaking like an AI is robbing us of language useful in critical thinking. I'm far more worried about people offloading their critical thinking to AI systems and losing the habit.
Also, the Greeks were worried about rhetoric and, in my opinion, rightly so. The skill to argue a point well is different than those that are needed to be correct. To become a skilled rhetoritician was viewed as dangerous (and right now AIs are only moderately good... though they are improving fast).
It’s unlikely this is true. LLMs are way more mad-libs / templates than we like to admit, that’s (ironically) not a judgement about their capability, it’s primarily just an observation. But it’s also what plain old SFT, which I believe is the primary culprit, ends up imparting.
Surely these leading tells will be trained out of models pretty soon, given how well known and overused they are. And it might make the writing slightly worse in a way. But it is quite annoying how often this type of construction is used in everything at the moment.
I think that the current models are still like over-achieving savants rather than true human level because the largest model is only 1/10th the complexity of the human brain. I've recently become fairly convinced that new hardware paradigms (like types of CIM) are about to move from research into real-world development and scaling. So I believe within a few years, the model sizes will increase by another 10 times.
Compared to upcoming 100 trillion parameter models, humans will obviously be _much_ dumber/slower than AI in all fields. Already with the 10T models, some LLMs beat 99.9% of humans in competitive programming.
The AI hatred from many may actually continue to increase, but in cases where the bottom line matters, we are rapidly approaching the point where writing or work product that looks like it is human-authored will be suspect just on that basis. In other words, for some people it will be the reverse -- "this work looks like it was created by a human" could be devastating for your businesses credibility at that point.
This is how early forms of "reasoning" in LLMs worked: just literally inserting words like "Wait...", "Hmm...", "Let me reconsider...", "But is it really..." into the token stream.
Is this not how current forms of reasoning work? It seems like the open models still output things like that, and the closed ones all just summarize their thinking instead to avoid distillation, but probably do the same thing internally.
I think the basic idea is the same (not being a frontier lab researcher I couldn’t say for sure), but there are different techniques, such as “reasoning tokens” that aren’t literally words, and more interesting structures than just sticking them into the stream.
For everyone claiming that this is a trope of LLM text because it is a trope in the training data: how do you know this trope doesn't emerge during RLHF?
nice article, but i think as a non native english speaker, i always use the model in english for reasoning and then translate the output to my language. most of these considerations do not apply. because the translation step is taking out alot of these language artifacts
Do you manually translate or translate with an LLM? While reading, I was wondering how common these kinds of written tics are in languages outside English.
In my experience, and as someone who has technically been a professional copy editor before (in the sense that I got paid by someone to perform line/copy editing of some material or other, but definitely not who or what you would think if I only said I used to be a copy editor), the uses of "not only, but also" that didn't have anything wrong with them (or didn't deviate from convention, if you like) were in the minority by far. Assuming people in the last few years haven't all become suddenly interested in that particular construction and skilled in its use, the presence of an improperly implemented NOBA should remain vaguely reliable as an indicator of authenticity :D
TLDR - it's not just AI detection. It's policing of human thought.
Anyway, yeah, people trusting AI to do a better job in reasoning than fellow humans, without justification, worries me. We have no formal theory of informal reasoning (that LLMs mimic), so we cannot verify it any better than with humans.
You have to trust someone, to ground your beliefs. Trusting AI is just trusting some other people (who trained it) by proxy. Once you realize it, you might as well try to trust people you know.
I'm not dropping emdashes -- though you can always tell mine by their two-hyphen form lol
I've also never used an AI detector, and probably never will.
In my experience:
1. The people who rely the most on AI writing don't like to admit it. I catch obvious AI hallucinations in my boss's "documentation," and he always insists it was his own human oversight, despite it being very obviously a mistake I've caught Claude (and importantly, no human coworker) making repeatedly
2. I don't trust a machine more than myself to judge writing
3. Obvious AI "tells" just make it clear i don't need to keep reading, not that i need some kind of validation. In some sense, i guess that might save me time? But i still have to have read enough to know what it is...
In general, i think the author makes great points about how _LLM "thinking" is just the reproduction of the language of reasoning_, that is not necessarily a replacement for actual reasoning. It'll take a lot more than that for me to believe an AI is "thinking" and not just giving statistically reasonable answers (reasonable or actionable though they may be)
> In the end, shaming people for writing that gets flagged as AI can lead people to sidestep structures the model has learned from us
It's interesting why LLMs generate constructions like this more frequently than they presumably exist in the training set. I wonder if this is some sort of mode collapse caused by post training, and/or maybe because they are training on synthetic data so these things become self-perpetuating and self-amplifying (a feedback loop)?
The lesson for humans worried about being falsely identified as AI is just learn to write better! It doesn't matter where your repertoire of phrasing comes from (copying AI or not), but one of the basic rules of writing is not to repeat yourself unless you are doing so deliberately for a purpose. Go ahead and use "It's not just X. It's Y" if you want to, but if you use it multiple times in the same short piece of writing, then you may deserve to be called out for poor style, if not for being an AI.
Its not model collapse nor does it have anything to do with training data frequency. It's simply RLHF where the humans hired to tune the conversational style of these LLMs preferred certain idioms over others and so the reward function for these LLMs gravitated toward using them.
If LLMs generated text based on training data frequency they'd likely be some of the most vulgar and hostile things ever created. The internet is full of insults, profanity, and low effort content. The repeated phrases are a side effect of reward optimization rather than some kind of model collapse.
An old xkcd comic that is somewhat related to the current witch hunt that some text that the author claims he wrote himself was actually written by an AI:
Problem is, everything gets poisoned by AI these days, and it gets worse when there's some sort of reward attached. Karma points in the case of Reddit and HN, in Wikipedia you got a ton of commercial actors and propaganda/distortion campaigns.
And that's why everyone on the receiving end of the AI slop deluge is so paranoid.
> Because if Pangram's AI system found me guilty, that's the end of my career. That's literally extortion.
How is this different from humans? When I went to high school, my teachers extorted me too. Especially subjects like English and unlike Math, where evaluation is 100% subjective.
I don't how the English evaluation works in the average (US?) school, or even what's in the exams. But it's possible to have useful native language exams with objective evaluation.
Until 2006, the national Finnish/Swedish (as a native language) exam at the end of high school in Finland consisted of two essays. One was based on materials that were provided, and another on a topic that was given. I believe there were a few options to choose from. Both essays were scored independently, and your score was the better of the two. If you had learned to write essays, it was effectively an intelligence test and a good predictor of future academic success across many fields.
Including CS, as my department found out. In particular, the ability to write essays was a better predictor of success in CS studies than the scores in mathematics and natural sciences. Probably because there has always been a large subset of CS students who are otherwise good at CS but can't handle anything resembling mathematics.
"Hyphen functioning as an em dash" is an expected human thing as it's what's easy to type. It's specifically an actual em dash which got bulldozed, much to the dismay of those who bothered to put the unicode character in.
If you read The Mac is Not a Typewriter in 1992—thus burning Option-Shift-hyphen into your typing patterns for life, along with a dogmatic love for serif body fonts—you're the real victim here.
Or those of us that use a full featured editor when writing md!
This reminds me of another em dash+AI related topic: I've noticed LLMs have an extreme bias towards spaces around the dash while people can go either way with it.
A signal is not the same thing as a guarantee. Both of your points so far, i.e. your provided text & that bots often bother to replace em dashes to avoid detection, actually support that it is a signal though.
The stronger yet signal is both combined! This glyph, that emoji, a given sentence structure, that formatting, a certain phrase. The more you notice -> the stronger the signal, the more you miss/discard -> the weaker the signal.
Alternatively, no one sounds like an llm, an llm sounds like someone, typically those close to the median of the training corpus. If AI were genuinly capable of novelty, it would be a big deal, tech bros having enough work ethic to design new detectable prose for an llm is a mssive reach and has no real evidence supporting it, else why do tech bros only tackle the easier issues? Things we have massive well labelled corpi for? Why is it never dishwashing and folding laundry?
I put to you, if you see a trope in AI writing it's because that trope appeared in the training corpus. Therefore, sure, being predjudice against it lets you catch some AI, but you'll also flag human outout. I think that may not be worth it in the end.
That is actually what I'm firmly convinced is the most dangerous thing about llm's. No matter what you put, it will always agree with you, and what's worse, it will try to make you think that you're unbelievably smart for saying x.
I used one to help me plan a sales route, and it kept fucking it up. Every time I corrected it, it tried that hand wringing vizier sort of ass kissing. It's very off-putting, but I can see how someone struggling with social interaction could be sucked into that nonsense.
For what it's worth (or maybe just for the record) I have a counterexample: Gemini once dug in its heels and insisted that some ebay listings for GPUs were scams because the cards they were selling hadn't been released yet (they had been, but its training data was too old, I assume).
I went a few rounds with it and it kept pushing back, which was odd for sure, as I'm also used to being able to essentially just say "no, x = 2". There was a lot happening in that session (it was really someone else's and he just kind of lets his context windows fill up with all sorts of stuff), so I bet it would have sufficed to start a new one, but after a point I just wanted to see what would happen. It didn't concede until I sent it a PDF of some kind of white paper or tech spec sheet or something that included release dates from an authoritative source.
I may need to find that session later, because now I'm wondering if it was entirely the PDF that did it, or if it also helped to point out that the info cutoff could be a factor, and I don't remember whether I tried the latter first.
Also not sure off the top of my head what the situation was as far as model, custom instructions, or whatever else.
Not always or inherently, I would say, but if you can't help consciously noticing how much a piece uses tricolons, or negative parallel constructions, or dashes offsetting punchy clauses at the ends of sentences, then the style has probably become what you might call overseasoned
"So, if we publicly shame people whose text looks like it might have been written by a machine – because it mimics the language used for human reasoning – and people stop writing in ways that they internalize as "AI writing" out of fear of false detection, it sends a signal that your language for reasoning must be policed, or you too could be held up to public scrutiny."
This is honestly both terrifying and well articulated.
High praise to the blog author.
There are plenty of idioms, find a different idiom, tough titties.
Surely it hasn't escaped your notice that the LLMs don't tend to stick to just the one set of idioms/devices. They're constantly running new batches of them into the ground
It's not just "It's not just X; it's Y", it's other stuff too
Congratulations, you've made the meme recursive.
This is honestly a very, very naive statement. We are social animals and we naturally gravitate towards devaluing and shaming certain styles of speech. We police speech already! It’s often unfortunate, but it’s not devoid of function. I, for one, am happy with shaming LLM speech. It’s never been so easy to detect lazy thinking.
What do you think about TFA and its contention that perfectly normal language is being targeted by the AI witch-hunt?
I personally avoid the em dash, but it has been used in writing for a long, long time.
Frankly, when humans produce empty reasoning like sentences with little reason behind them, we should be allowed to call it a slop too.
no its not terrifying. its just raising the level of writing, if you are using not x but y then you fucking better justify the need to use a negation
Last week I read through 10 project proposals by students. Two of those ticked all boxes for LLM writing throughout their full text. Not that I checked for LLM-markers specifically, but if a text makes you go: wait a minute, am I reading the output of an LLM? only to then present you with more markers also content-wise, that will have an impact on the human reading the text.
And it should. If someone sends me an obvious copy-paste mass email it also has an impact on how serious I take that email to be meant as an actionable proposal targeted at me specifically.
If they half-ass their proposal which has to do with language I can reasonably infer they may also half-ass the real world implementation which in this case also had to do with language. If you're unable to describe your own idea on half a page of paper in your own words, maybe the students who are able to do so should be treated fair.
I don't care wheter or not they use LLMs, in fact do. But engage with the ideas and results and convince me you really care about them.
It's easy to focus in on particular linguistic tics, which will probably get smoothed away in future training. The underlying issue is that the LLM is trying to ape meaningful writing - which takes the reader from A to a surprising Z - without generally basing it on a meaningful insight.
Most of the common tells stem from that desire to signal the gap between what it's writing about now and how you previously thought things worked. And they really fall flat when it's writing about some milquetoast truism with all the edges sanded off.
Rather than have "Z" be self-evidently interesting, the LLM need to tell us that it's not "A". Except no one thought anything was "A" in the first place, and the "Z" is barely a "B" let alone a "Z".
Or things are "quietly X," implying that there is some secret knowledge that other people have.
Barring that, the LLM will signpost arguments, telling you how interesting things are. "This is the critical part..." before launching into another banal non-observation. Why have only "Section Header" when you can have "Section Header (another idea I had) - omg I just have so much to say about this". Maybe a list of weak ideas, presented in multiple ways. Bulleted with emojis. As a rule of three. As choppy sentences in a paragraph.
All of these follow the same pattern - trying to follow the FORM of having something interesting to say that differs from consensus understanding, without having the intelligence or boldness to actually midwife a new concept into the world.
AI output reads like homepage marketing content (e.g. the text that fades in when you scroll down an apple product page) expanded to fill some context window size (the paragraphs tend to be about the same size).
What you get is vacuous, choppy, wordy, and hyperbolic. I have found that adding secondary passes for tone and style improve the readability dramatically.
It strikes me as an Oder of operations problem.
If the system prompt is “flesh out template y with thought x” the form drives the generation, it feels compelled to use the whole template.
Of the system prompt is “refine thought x and then format it with the appropriate parts of template y” it becomes a simple transformation and formatting.
A lot of current gen llm pain appears to be being in the early days of understanding the nuance of system prompts.
Totally agree, I think it can get there.
If you present the idea as "an idea" rather than "my idea", it's pretty good at challenging, solidifying, and refining it. It still leans on the same forms in the writing part, but I think it can be tuned to not insist upon the idea's brilliance so breathlessly.
Yes, this is the kind of thing I've been hoping more people would notice.
I think another tell with a long lifespan is that it will try to write about a thing it experienced, but having no real knowledge of the qualia, it'll end up only referring to it (not uncommonly using "that") and leaving all the substance as an exercise for the reader
I like that these AI idioms exist. They're like watermarks for text. It's worth the cost of humans avoiding them. Companies will eventually train their models to be undetectable, but society would be better if they didn't.
Except that the entire point of the article is that they're not AI idioms. They're not "watermarks for text." They're legitimate language constructions that LLMs tend to overuse, but that real humans also use. Real humans do, in fact, say "align with" all the time, just as often as "corresponds."
And you can pry my em dashes from my cold, dead hands.
Well reading between the lines I don’t think they’re saying all of those uses are AI. They’re legitimate constructs, like the em-dash, en-dash, and hyphen, all of which I used to use regularly. But now they’re AI tells so I use them sparingly.
Sociolinguistic register happened.
The article is not God, just because it claims something doesn't mean we have to accept it.
For better or worse (and pretty much for worse), these usages have become AI idioms. Language evolves over time, things that used to be harmless become offensive, certain terms end up taking on the complete opposite meaning than their original meaning, and we are watching certain language patterns and idioms become watermarks for AI and while it sucks, it doesn't make it false.
I'll just quote from the article, which no one claimed was God and that's really a weird way to dismiss it, but you do you:
"We create a culture of self-censorship and AI-detector-pressured rewriting and paraphrasing as people strive to avoid these witch hunts. That is the opposite of protecting human expression. We should resist normalizing a trust in any machine's ability to determine matters of guilt. If using AI to write is, at its worst, an industrialization of the mind, then AI detection, at its worst, becomes a surveillance system for thought."
And, I'm sorry (I'm not), but I am not going to just roll over and shrug and say "welp, guess we all need to dumb our writing down to keep well-meaning idiots from screeching 'AI! AI! AI! WHOOP! WHOOP WHOOP WHOOP!' at us." That isn't the evolution of language. It's Idiocracy.
What's worse is neurodivergent writing, including my own, often resemble AI output. Now it feels like I'm having to alter my own voice in online discussions just to specifically avoid being accused of pasting an AI response.
The "AI Detection" tools employed by schools also regularly flag writing from those with Autism, ADHD, and non-native English speakers as being AI generated as well.
So, naturally, I can't stand the phrase "write like AI" when these things tend to come up because no, there are no humans that "write like AI" it's the models that have stolen the literary devices from us and now have poisoned them.
That is an empirical question. Do you have empirical sources you'd care to share?
Once upon a time, using em dashes—which hardly anyone knew how to conveniently invoke—was a fun writing quirk to have.
Now I'll have to find something else to overuse: maybe sentences structures around colons, or use of Japanese 「hook brackets」.
> It's worth the cost of humans avoiding them
That's really unfortunate though. It's like Michael Bolton from Office Space: "No way! Why should I change? He's the one who sucks."
I agree with the feeling. But if you agree with the analysis of the article, this cat & mouse game ultimately amounts to stop disclosing our reasoning threads through commonly accepted linguistic structures. That's quite a price to pay as a society...
It's like knowing to stay away from a Github repo because it has a readme that's full of emoji bullet points.
I thought I was the only one that did this. Double stay away if at the end you find out it was "made with love"
I just look for the CLAUDE.md or related.
I actually find the "AI idioms" rather less grating than emoji-vomit. That said, I don't know why certain LLM output seems to be full of the latter; certainly no real human writing I've seen has that style, but perhaps it's a result of training on data that probably should've been done without.
Patrick Wardle, the guy behind Objective-See, had that style in the 2010s when I first started following his work. I actually liked it at the time.
Humans are just trying to do what Pangram is trying to do: guess what is AI, badly. The post argues against this:
> In the end, shaming people for writing that gets flagged as AI can lead people to sidestep structures the model has learned from us: structures that are effective tools for argumentation. We take the tools of critical thinking out of the kit at the time we most need them.
This is my position with this stuff. It became part of the LLM loop because it’s used a lot- it’s used a lot because it’s effective.
Now we’re going to stop using effective rhetorical methods because they imply AI, even if we know we’re not using AI?
It reminds me of, as a teenager, asking my dad if he ever saw Led Zeppelin live. He hadn’t, because he didn’t really like fans of Led Zeppelin and didn’t want to be associated with them.
As an ashamed fan of certain bands I get this instinct but I also promised to myself when I heard this that I would do my best to not allow other people to influence how I thought about things I enjoyed.
On the same note I’m trying to be “braver” about things like em-dashes, though my personally style has always been to use them as I did in this comment- like this, which I guess distinguishes me, until an LLM picks that up too…
An em dash looks like this
—
You're not using that, neither in the past from what I can tell, nor in this comment.
You're just using a hyphen/minus instead of a colon, that's not an llm-ism
In fact, I'd say it's a dead giveaway for "human impersonating AI impersonating humans". Using the hyphen as an em dash screams
I like to use a lazy variant -- it's not a double dash, or a weirdly written plus, it's a an em-dash that says "I don't even have this key on my keyboard, are you actually using alt-codes or what am I missing?". Not with a shout or a whisper, but with the quiet courage of just being -- but not an incomplete representation of a whole, but rather the fullness of that very distillation of honest, simple pragmatism. Not less, just different.
The above isn't slop. It's shit though!
Actually, in an ancient and venerable markup language that's still in wide use in certain not-unimportant communities:
- = hyphen
-- = n-dash
--- = m-dash
I don’t think it’s quite the same though. The way it constructs thoughts is very algorithmic. If you look at the Wikipedia ai text doc it’s a much better explanation and arguments for not immediately blaming someone for using ai.
https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
I don't think so at all. Models are trained in many ways and are changing aggressively, resulting in different patterns in different regions, domains, languages, and will be different 3, 5, 10 years down the line. Having everyone try to learn and adapt around how to stay within very magical, fuzzy, and ever-changing boundaries to avoid appearing to be an AI, instead of focusing on producing good writing or communicating as it is natural to them, seems like a recipe for bad thinking and arbitrary reactions.
> will be different 3, 5, 10 years down the line.
Possibly, but it's not a necessity. Click baiting (i.e. yt videos) has evolved to stable standards, that's at least my impression.
Also, products often only get improved until they are "good enough", not until they are "good". It happens, but then they just iterate towards the "how bad can I become" baseline from the other side.
AI companies generally are not in the "let's make the best AI possible" business but in the "let's make the most money" business. This just hasn't fully manifest because they get flooded with VC.
Telling humans to change how they write just so they won’t be accused of using AI is the most anti-human pro-AI idea imaginable.
AGI Plan to end humanity, act I: communicate so well they will start to communicate horribly, setting back their collective IQ by thousands of years.
Could just as well be AGI's plan to save humanity.
Counterpoint: I think it can also useful to avoid LLM-isms because it's a quick test to check whether you're saying something derivative or actually saying something novel/interesting/significant. Which is to say, if someone could credibly accuse me of being an LLM, then that means my writing is no better (for whatever definition of "better" you want to use) than what happens when you melt down all of human language into a paste and then reconstitute it into featureless little cubes.
Obviously there are exceptions; you can use certain constructions in a way that's still unmistakably human, or use them within a larger context of unmistakably human writing. But in general it makes me think about Orwell's argument against cliches:
> A newly invented metaphor assists thought by evoking a visual image, while on the other hand a metaphor which is technically ‘dead’ (e. g. iron resolution) has in effect reverted to being an ordinary word and can generally be used without loss of vividness. But in between these two classes there is a huge dump of worn-out metaphors which have lost all evocative power and are merely used because they save people the trouble of inventing phrases for themselves.
If LLM-isms give readers the impression that I'm too lazy to phrase things in my own words, even if I did in fact phrase things in my own words, then I take that as a sign that I should pick better words!
Granted, I've had a strong desire to write as distinctly and un-cliche-ish-ly as possible since long before ChatGPT's public launch, so I might not be as grumbly as other commenters who feel like this would force them to change how they write.
A quick and broken test.
Clean. This comment is the right shape.
Nah pry my lists of 3 from my cold dead hands. And my emdashes sometime after that.
It's not X, it's Y, though? Couldn't be me.
I think the real tell is when Y~=X. It's just performative. Like genuinely formative (the other tell is real/actual/genuine over a weak claim).
i was just yesterday yelling at Gemini for telling me, five times in a row, that it "had found the absolute truth of the problem" when it was wrong all 5 times lol
It's a useful construction. "It's not true love, you matched with her on Hinge last week and have never met her, please don't send her $1000 in Apple gift cards" is punchy.
I utterly detest the idea of having AI potentially lock me out of my own writing style.
> It's worth the cost of humans avoiding them.
No, fuck that. I'm not going to think twice about what I write just to avoid an AI checker, and I will delve into em dashes with gusto if that's what the writing calls for.
I'm not sacrificing the language simply to sound less like AI--that's absolutely a losing game.
And if anyone thinks my hand-crafted prose is AI-generated, they're free to look elsewhere. Right now AI detectors peg my pre-AI work as 30% AI-generated, and I'm certain that number will only increase as LLMs improve.
> I'm not going to think twice about what I write just to avoid an AI checker
It depends on your environment, I guess. If you're a student writing an essay or a researcher writing a paper, it's in your best interest to avoid sounding like an LLM, which means going out of your way to avoid certain idioms, even if it means letting go of things you liked to write.
I used to love a spaced en dash (the British English equivalent of the American unspaced em dash), but I wouldn't risk it now.
I remember someone posting about the most human of all traits being reassuring to see: Typos. I'm pretty sure people are not as averse to leaving or finding typos in text as they were 5 years ago, as these days it's a signal of humanity.
Same has been applying to art for a while. Several artists who have an "AI-ish" style have been wrongfully crucified for using AI. And been forced to post videos of their process end to end, in order to prove that they aren't using AI. It's a thing for artists to post their new stuff with: "AI could never do this."
Slightly off topic, I'm not sure, but way back in the day (2000ish) a friend of mine used PERL scripts to scrape all the big databases which existed at the time, namely IMDB.
He used PERL for scraping and the same for generating "new" content with what he had scraped. He made a bunch of static websites with ads. The sites connected to each other. Sports, Celebrities, Movies, you name it. He had a formula.
Those sites were profitable enough that he could travel the world and have fun, basically. His mother collected the cheques from Google and cashed them into his account.
Now to get to the final point here, his secret was simply TYPO INJECTION to avoid Google's then embryotic duplicate content detection.
> There is danger in evaluating for language patterns over its content
I agree, but it’s worth noting that that has been done since long before LLMs. Fifteen years ago, I used to teach a graduate course on academic writing pedagogy. The students and I would read research papers on the teaching of academic writing; we also analyzed textbooks and course syllabuses to get an idea about what was actually being done in classrooms. While phrases like “critical thinking” did come up, the overall focus was clearly on language patterns: sentence and paragraph structure, the use of transition words, vocabulary for hedging and boosting (i.e., making assertions seem weaker or stronger), etc.
In a university context, it can be very difficult to evaluate student writing based on its content. In humanities-focused and creative writing, what the student decides to say can be seen as an extension of the student’s personality, identity, and individual experience; if a teacher evaluates the content, including the reasoning, it can seem that the teacher is evaluating the student as a person. And if the students are in the sciences, especially at the graduate level, the writing teacher often won’t even understand what the students write because it is too technical. Teaching and evaluating language patterns, not content, is often the only option.
In one of the essays posted here, which was, ironically, about AI in education, a sentence, that an AI could not possibly write, that I could possibly write, because of its length and unusual structure, before finally reaching the verb, went on for 25 words.
I don't know if it was written that way to show trust in the reader's intelligence, show disregard for reaching a wide audience, show a demonstration of skill, or was artifact of someone just thinking at that level.
Your first sentence is 45 words and contains 9 commas.
> I don't know if it was written that way to show trust in the reader's intelligence, show disregard for reaching a wide audience, show a demonstration of skill, or was artifact of someone just thinking at that level.
It's been a while since I've seen such a whoosh worthy comment.
The robot can be made to write any such thing
In the interest of not occupying significant page/screen height with LLM output, example prompts+responses here: https://dpaste.com/H9DXKNYQH.txt
https://fakewriters.onrender.com/ is a good example too
It's fine. People will always find something to be publicly unhappy about.
Example 1. Someone reached out to me on LinkedIn "from HN", when I replied to their initial message they just said "You look like an AI trawler" and disconnected.
Example 2. I read a popular non-English tech blog aggregator which also encourages comments and discussion. Since ~1.5 years ago every other comment is "thank you author, but if I wanted to read AI I would as AI" or some variation thereof.
Would it be some kind of "reverse psychosis"?
I think people overestimate the radius of avoidant behavior against AI idioms, and underestimate how the trove of AI generated text actually influence people's writing. It's not a one way street. If you mostly read AI generated content, your writing will inevitably resemble it.
People stopped actually reading when we dropped classical liberal education, right after WWII.
This is merely the end-state of industrialization, which is efficient and soulless.
I liked everything in this post, with one exception. I'm less sure that avoiding speaking like an AI is robbing us of language useful in critical thinking. I'm far more worried about people offloading their critical thinking to AI systems and losing the habit.
Also, the Greeks were worried about rhetoric and, in my opinion, rightly so. The skill to argue a point well is different than those that are needed to be correct. To become a skilled rhetoritician was viewed as dangerous (and right now AIs are only moderately good... though they are improving fast).
> RLVR is weirder, and I suspect it's why we see "It's not X, it's Y" so often.
This feels like an easy enough hypothesis to verify, for anyone in the business of training LLMs - does the not-X-but-Y rate increase after RLVR?
It’s unlikely this is true. LLMs are way more mad-libs / templates than we like to admit, that’s (ironically) not a judgement about their capability, it’s primarily just an observation. But it’s also what plain old SFT, which I believe is the primary culprit, ends up imparting.
Surely these leading tells will be trained out of models pretty soon, given how well known and overused they are. And it might make the writing slightly worse in a way. But it is quite annoying how often this type of construction is used in everything at the moment.
I think that the current models are still like over-achieving savants rather than true human level because the largest model is only 1/10th the complexity of the human brain. I've recently become fairly convinced that new hardware paradigms (like types of CIM) are about to move from research into real-world development and scaling. So I believe within a few years, the model sizes will increase by another 10 times.
Compared to upcoming 100 trillion parameter models, humans will obviously be _much_ dumber/slower than AI in all fields. Already with the 10T models, some LLMs beat 99.9% of humans in competitive programming.
The AI hatred from many may actually continue to increase, but in cases where the bottom line matters, we are rapidly approaching the point where writing or work product that looks like it is human-authored will be suspect just on that basis. In other words, for some people it will be the reverse -- "this work looks like it was created by a human" could be devastating for your businesses credibility at that point.
This is how early forms of "reasoning" in LLMs worked: just literally inserting words like "Wait...", "Hmm...", "Let me reconsider...", "But is it really..." into the token stream.
Is this not how current forms of reasoning work? It seems like the open models still output things like that, and the closed ones all just summarize their thinking instead to avoid distillation, but probably do the same thing internally.
I think the basic idea is the same (not being a frontier lab researcher I couldn’t say for sure), but there are different techniques, such as “reasoning tokens” that aren’t literally words, and more interesting structures than just sticking them into the stream.
It's bigger than that, it's large
https://youtu.be/1Pr8xnNi7OM
But are we the baddies?
https://youtu.be/ToKcmnrE5oY?is=-e0nPJsvkBD7DFI2
For everyone claiming that this is a trope of LLM text because it is a trope in the training data: how do you know this trope doesn't emerge during RLHF?
nice article, but i think as a non native english speaker, i always use the model in english for reasoning and then translate the output to my language. most of these considerations do not apply. because the translation step is taking out alot of these language artifacts
Do you manually translate or translate with an LLM? While reading, I was wondering how common these kinds of written tics are in languages outside English.
Clearly humans always type "it's not merely X, but also Y"
In my experience, and as someone who has technically been a professional copy editor before (in the sense that I got paid by someone to perform line/copy editing of some material or other, but definitely not who or what you would think if I only said I used to be a copy editor), the uses of "not only, but also" that didn't have anything wrong with them (or didn't deviate from convention, if you like) were in the minority by far. Assuming people in the last few years haven't all become suddenly interested in that particular construction and skilled in its use, the presence of an improperly implemented NOBA should remain vaguely reliable as an indicator of authenticity :D
I stopped reading at "Nerd rating".
TLDR - it's not just AI detection. It's policing of human thought.
Anyway, yeah, people trusting AI to do a better job in reasoning than fellow humans, without justification, worries me. We have no formal theory of informal reasoning (that LLMs mimic), so we cannot verify it any better than with humans.
You have to trust someone, to ground your beliefs. Trusting AI is just trusting some other people (who trained it) by proxy. Once you realize it, you might as well try to trust people you know.
I'm not dropping emdashes -- though you can always tell mine by their two-hyphen form lol
I've also never used an AI detector, and probably never will.
In my experience:
1. The people who rely the most on AI writing don't like to admit it. I catch obvious AI hallucinations in my boss's "documentation," and he always insists it was his own human oversight, despite it being very obviously a mistake I've caught Claude (and importantly, no human coworker) making repeatedly
2. I don't trust a machine more than myself to judge writing
3. Obvious AI "tells" just make it clear i don't need to keep reading, not that i need some kind of validation. In some sense, i guess that might save me time? But i still have to have read enough to know what it is...
In general, i think the author makes great points about how _LLM "thinking" is just the reproduction of the language of reasoning_, that is not necessarily a replacement for actual reasoning. It'll take a lot more than that for me to believe an AI is "thinking" and not just giving statistically reasonable answers (reasonable or actionable though they may be)
> In the end, shaming people for writing that gets flagged as AI can lead people to sidestep structures the model has learned from us
It's interesting why LLMs generate constructions like this more frequently than they presumably exist in the training set. I wonder if this is some sort of mode collapse caused by post training, and/or maybe because they are training on synthetic data so these things become self-perpetuating and self-amplifying (a feedback loop)?
The lesson for humans worried about being falsely identified as AI is just learn to write better! It doesn't matter where your repertoire of phrasing comes from (copying AI or not), but one of the basic rules of writing is not to repeat yourself unless you are doing so deliberately for a purpose. Go ahead and use "It's not just X. It's Y" if you want to, but if you use it multiple times in the same short piece of writing, then you may deserve to be called out for poor style, if not for being an AI.
Its not model collapse nor does it have anything to do with training data frequency. It's simply RLHF where the humans hired to tune the conversational style of these LLMs preferred certain idioms over others and so the reward function for these LLMs gravitated toward using them.
If LLMs generated text based on training data frequency they'd likely be some of the most vulgar and hostile things ever created. The internet is full of insults, profanity, and low effort content. The repeated phrases are a side effect of reward optimization rather than some kind of model collapse.
this article is great. we need to protect our ways of thinking, and it's going to be -- already is -- extremely difficult
An old xkcd comic that is somewhat related to the current witch hunt that some text that the author claims he wrote himself was actually written by an AI:
https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing#...
Signs? Those are normal ways of writing? What the hell? Is everything AI now?
Problem is, everything gets poisoned by AI these days, and it gets worse when there's some sort of reward attached. Karma points in the case of Reddit and HN, in Wikipedia you got a ton of commercial actors and propaganda/distortion campaigns.
And that's why everyone on the receiving end of the AI slop deluge is so paranoid.
Did you read it though? They explain very well their reasoning with real examples.
An excellent article that perfectly articulates the absurdity of focusing on style of writing over content.
You’re absolutely right to push back on this.
Sometimes it’s not just about the Ys but also the Qs.
We solved this problem already with the antislop sampler: https://arxiv.org/abs/2510.15061
> Because if Pangram's AI system found me guilty, that's the end of my career. That's literally extortion.
How is this different from humans? When I went to high school, my teachers extorted me too. Especially subjects like English and unlike Math, where evaluation is 100% subjective.
I don't how the English evaluation works in the average (US?) school, or even what's in the exams. But it's possible to have useful native language exams with objective evaluation.
Until 2006, the national Finnish/Swedish (as a native language) exam at the end of high school in Finland consisted of two essays. One was based on materials that were provided, and another on a topic that was given. I believe there were a few options to choose from. Both essays were scored independently, and your score was the better of the two. If you had learned to write essays, it was effectively an intelligence test and a good predictor of future academic success across many fields.
Including CS, as my department found out. In particular, the ability to write essays was a better predictor of success in CS studies than the scores in mathematics and natural sciences. Probably because there has always been a large subset of CS students who are otherwise good at CS but can't handle anything resembling mathematics.
Another bunch of dead give aways in code bases with READMEs is the repetitive:
- "No X, No Y, No Z." pattern
- "Here is X - it makes Y"
The worst and most obvious one is the constant over use of emoji ticks and crosses.
For calibration purposes, I offer you a pre-LLM README I wrote that includes an em-dash* followed by "No X, No Y, No Z": https://github.com/DavidBuchanan314/stelf-loader
*actually a hyphen but it's functioning as an em dash.
"Hyphen functioning as an em dash" is an expected human thing as it's what's easy to type. It's specifically an actual em dash which got bulldozed, much to the dismay of those who bothered to put the unicode character in.
If you read The Mac is Not a Typewriter in 1992—thus burning Option-Shift-hyphen into your typing patterns for life, along with a dogmatic love for serif body fonts—you're the real victim here.
Or those of us that use a full featured editor when writing md!
This reminds me of another em dash+AI related topic: I've noticed LLMs have an extreme bias towards spaces around the dash while people can go either way with it.
There's something similar in Microsoft Word, Ctrl-Alt-Minus on the numpad.
I remember that being how you shut off turbo mode on your XT clone in DOS.
I prefer the double dash "--", but Microsoft products will convert this to a proper em-dash if you press space afterwards, I think...
Double should map to endash, tripple for em.
A lot of the LLM bots on HN (and elsewhere) will find-and-replace their em dashes with hypens in an attempt to evade detection.
Precisely, anything to remove AI smells in favor of natural looking text.
My point is I don't consider em dash vs hyphen to be a strong signal either way, humans and bots alike use both interchangeably.
A signal is not the same thing as a guarantee. Both of your points so far, i.e. your provided text & that bots often bother to replace em dashes to avoid detection, actually support that it is a signal though.
The stronger signal is the grammatical structure, not the specific glyph used.
The stronger yet signal is both combined! This glyph, that emoji, a given sentence structure, that formatting, a certain phrase. The more you notice -> the stronger the signal, the more you miss/discard -> the weaker the signal.
and we will now hold you responsible!
Alternatively, no one sounds like an llm, an llm sounds like someone, typically those close to the median of the training corpus. If AI were genuinly capable of novelty, it would be a big deal, tech bros having enough work ethic to design new detectable prose for an llm is a mssive reach and has no real evidence supporting it, else why do tech bros only tackle the easier issues? Things we have massive well labelled corpi for? Why is it never dishwashing and folding laundry?
I put to you, if you see a trope in AI writing it's because that trope appeared in the training corpus. Therefore, sure, being predjudice against it lets you catch some AI, but you'll also flag human outout. I think that may not be worth it in the end.
Show me a single substantial (5000+ words) piece of writing from before the release of GPT-3 that triggers Pangram with high confidence.
/* This function doesn't return an int. It doesn't return a float. It doesn't return a char. It doesn't ret-- */
I've seen AI-generated API documentation do this: "Good for X and Y. Do NOT use for Z - use foo instead."
A human writer would add that sparingly, for cases where there might be some ambiguity. But the bot added that to basically every single API endpoint.
You’re absolutely right. This is the smoking gun. This changes everything.
This is the real unlock. Here's the key takeaways.
It's not just an unlock. It's a major discovery.
Now I see the full picture.
I'm zeroing in on the main culprit.
Wait, there could be more things to consider.
This is the crux of the analysis.
That is actually what I'm firmly convinced is the most dangerous thing about llm's. No matter what you put, it will always agree with you, and what's worse, it will try to make you think that you're unbelievably smart for saying x.
I used one to help me plan a sales route, and it kept fucking it up. Every time I corrected it, it tried that hand wringing vizier sort of ass kissing. It's very off-putting, but I can see how someone struggling with social interaction could be sucked into that nonsense.
My custom instructions to ChatGPT starts with "Never apologize", which seems to work.
For what it's worth (or maybe just for the record) I have a counterexample: Gemini once dug in its heels and insisted that some ebay listings for GPUs were scams because the cards they were selling hadn't been released yet (they had been, but its training data was too old, I assume).
I went a few rounds with it and it kept pushing back, which was odd for sure, as I'm also used to being able to essentially just say "no, x = 2". There was a lot happening in that session (it was really someone else's and he just kind of lets his context windows fill up with all sorts of stuff), so I bet it would have sufficed to start a new one, but after a point I just wanted to see what would happen. It didn't concede until I sent it a PDF of some kind of white paper or tech spec sheet or something that included release dates from an authoritative source.
I may need to find that session later, because now I'm wondering if it was entirely the PDF that did it, or if it also helped to point out that the info cutoff could be a factor, and I don't remember whether I tried the latter first.
Also not sure off the top of my head what the situation was as far as model, custom instructions, or whatever else.
>Recent overuse by language models has led many to declare it bad writing. I'm not so sure.
It is bad writing.
Always? There's never a place for it?
Not always or inherently, I would say, but if you can't help consciously noticing how much a piece uses tricolons, or negative parallel constructions, or dashes offsetting punchy clauses at the ends of sentences, then the style has probably become what you might call overseasoned
I'd say it's average writing.