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It's Not Just X. It's Y

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Re: It's Not Just X. It's Y

#151
post #59

> 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 cl…

Curious about this approach to writing criticism. What authors informed the course? What were the course’s main text(s)?

The focus of the course wasn't writing criticism or particular authors. It was on how writing teachers can teach current and future researchers how to write research papers. A narrow field, perhaps, but at the research university where I worked there was demand for such writing courses, and my class looked at how such classes can be taught at a meta level. Many of the students themselves became writing teachers.

This was all before LLMs. The assumptions behind my class have since been upended, now that easily available chatbots can produce academic writing that, at least at the structural level, is perfectly fine.

Re: It's Not Just X. It's Y

#153

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…

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.

Marketing content without a reader persona or a writer persona, or rather, without the backing of a real consciousness with agency and life experience. I wonder if this might be part of why there are waves of different tells (in addition to the model updates): People pick up on an uncanniness in the writing but aren't fully aware of it or its nature, so they seek indicators and find what's there to find at the time

Re: It's Not Just X. It's Y

#154
post #150

Earlier quoted context omitted.

> 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 equ…

Eventually, though, you won't be able to avoid it.

You're right, of course. But today, it's not a risk worth taking, at least not for professional writing where the suspicion of LLM writing can be damning.

Re: It's Not Just X. It's Y

#155
post #80

Earlier quoted context omitted.

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 c…

Show me a single substantial (5000+ words) piece of writing from before the release of GPT-3 that triggers Pangram with high confidence.

Burden of proof that ai tools aren't dogshit isn't really on me, so pipe down and use a more reasonable register you pissant. This site, even this thread is filled with evidence. You're in no position to demand anything, especially not something apparently demanded in bad faith. A request for info I'd be happy to meet, but not this.

There are many cases out there of people proving that it does happen. I have personal text not published that do trigger all detectors between 70-100% AI depending on the tool. I wont be sharing these, as "providers" of these "tools" would simply add it to training data and continue to merrily overfit.

Bottom line, transformers regress to the mean like many other models, if you as a person produce output aligned with mean of corpus, you'll trigger detection. More importantly, evading detectors is trivial. Find a corpus of text from an author, get an llm to write a note on style, parlance, habits in writing etc. and then use that voice file to drive outputs from an llm. If the source text didnt register as AI, the new ai output also reliably avoids detection.

So my problem is, detection doesnt work, false positives are fact, so these tools at best offer harm.

A bigger problem¸ undermining your request for proof beyond that which many before me, and including me, burned in an effort to make folks see reason, is that even if i handed you proof on a silver platter you wouldnt understand it. If you could, you'd already understand, because the problem and the math are quite simple. Every example text i've offered in the past now registers 100% human, but many I kept to myself continue to show the same problem, and that never changed. So why would I waste my few remaining tools for sanity checking, when all i can expect from that endevour is losing a tool and shifting nothing in the conversation? No, best I keep that to myself for now.

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