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I would never claim that we can reliably detect all AI generated text. There are many ways to write text with LLM assistance that is indistinguishable from hum

I would never claim that we can reliably detect all AI generated text. There are many ways to write text with LLM assistance that is indistinguishable from human output. Moreover, models themselves are extremely bad at detecting AI-generated text, and it is relatively easy to edit these tells out if you know what to look for (one can try to prompt them out too, though success is more limited there). I am happy to make a much narrower claim, however: each particular set of models, when not heavily prompted to do otherwise, has a "house style" that's pretty easily identifiable by humans in long-form writing samples, and content written with that house style has a very high chance of being generated by AI. When text is written in this house style, it is often a sign that not only were LLMs used in its generation, but the person doing the generation did not bother to do much editing or use a more sophisticated prompt that wouldn't result in such obvious tells, which is why the style is commonly associated with "slop." I find it interesting that you believe this claim is wildly conspirational, or that you think the difficulty of reliably detecting AI generated text at scale is evidence that humans can't do pretty well at this much more limited task. Do you also find claims that AIs are frequently sycophantic in ways that humans are not, or that they will use phrases like "you're absolutely right!" far more than a human would unless prompted otherwise (which are the exact same type of narrow claim) similarly conspirational? i.e., is your assertion that people would have difficulty differentiating between a real human's response to a prompt and Claude's response to a prompt when there was no specific pre-prompt trying to control the writing style of the response?

dpark 11mo ago
On the other fork where I responded to your claims with a direct and detailed response, you insisted that my comment “isn't really that interesting” and just disengaged. I’m not going to write another detailed explanation of why your “slop === AI” premise is flawed. Go reread the other fork if you’ve decided you’re interested. > I find it interesting that you believe this claim is wildly conspirational I don’t believe it’s wildly conspiratorial. I believe it’s foolishly conspiratorial. There’s some weird hubris in believing that you (and whatever group you identify as “us”) are able to deterministically identify AI text when experts can’t do it. If you could actually do it you’d probably sell it as a product.
- MobiusHorizons 11mo ago
  > believing that you (and whatever group you identify as “us”) are able to deterministically identify AI text I think you will find the OP said no such thing. They instead said they identified a mixture of writing styles consistent with a human author and an LLM. The OP says nothing about deterministically identifying LLMs, only that the style of specific sections is consistent with LLMs leading to the conclusion.
  - dpark 11mo ago
    I think you find OP absolutely did say that. > Parts of it were 100% LLM written. Like it or not, people can recognize LLM-generated text pretty easily https://news.ycombinator.com/item?id=45868782 https://news.ycombinator.com/item?id=45868782
    - Jweb_Guru 11mo ago
      I am pretty much certain that parts of it were LLM-written, yes. This doesn't imply that the entire blog post is LLM-generated. If you're a good Bayesian and object to my use of "100%" feel free to pretend that I said something like "95%" instead. I cannot rule out possibilities like, for example, a human deliberately writing in the style of an LLM to trick people, or a human who uses LLMs so frequently that their writing style has become very close to LLM writing (something I mentioned as a possibility in an earlier reply; for various reasons, including the uneven distribution of the LLM-isms, I think that's unlikely here).
    - MobiusHorizons 11mo ago
      Thanks for adding the quote, that is a different part of the post than I was focusing on. I still think that's a far cry from deterministically recognizing LLM-generated text. At least the way I would understand that would be an algorithmic test with very low rates of both false positives and false negatives. Instead I understood the OP to be saying that people have an intuitive sense of LLM generated text with a relatively low false negative rate. I am certain that the skill varies widely between individuals, but in principle there is no reason to suspect that with training humans could not become quite good at recognizing low effort (no attempt at altering style) LLM generated content from the major models. In principle it is no different than authorship analysis used in digital forensics, a field that shows fairly high accuracy under similar conditions.

dpark 11mo ago

On the other fork where I responded to your claims with a direct and detailed response, you insisted that my comment “isn't really that interesting” and just disengaged. I’m not going to write another detailed explanation of why your “slop === AI” premise is flawed. Go reread the other fork if you’ve decided you’re interested. > I find it interesting that you believe this claim is wildly conspirational I don’t believe it’s wildly conspiratorial. I believe it’s foolishly conspiratorial. There’s some weird hubris in believing that you (and whatever group you identify as “us”) are able to deterministically identify AI text when experts can’t do it. If you could actually do it you’d probably sell it as a product.

MobiusHorizons 11mo ago
> believing that you (and whatever group you identify as “us”) are able to deterministically identify AI text I think you will find the OP said no such thing. They instead said they identified a mixture of writing styles consistent with a human author and an LLM. The OP says nothing about deterministically identifying LLMs, only that the style of specific sections is consistent with LLMs leading to the conclusion.
- dpark 11mo ago
  I think you find OP absolutely did say that. > Parts of it were 100% LLM written. Like it or not, people can recognize LLM-generated text pretty easily https://news.ycombinator.com/item?id=45868782 https://news.ycombinator.com/item?id=45868782
  - Jweb_Guru 11mo ago
    I am pretty much certain that parts of it were LLM-written, yes. This doesn't imply that the entire blog post is LLM-generated. If you're a good Bayesian and object to my use of "100%" feel free to pretend that I said something like "95%" instead. I cannot rule out possibilities like, for example, a human deliberately writing in the style of an LLM to trick people, or a human who uses LLMs so frequently that their writing style has become very close to LLM writing (something I mentioned as a possibility in an earlier reply; for various reasons, including the uneven distribution of the LLM-isms, I think that's unlikely here).
  - MobiusHorizons 11mo ago
    Thanks for adding the quote, that is a different part of the post than I was focusing on. I still think that's a far cry from deterministically recognizing LLM-generated text. At least the way I would understand that would be an algorithmic test with very low rates of both false positives and false negatives. Instead I understood the OP to be saying that people have an intuitive sense of LLM generated text with a relatively low false negative rate. I am certain that the skill varies widely between individuals, but in principle there is no reason to suspect that with training humans could not become quite good at recognizing low effort (no attempt at altering style) LLM generated content from the major models. In principle it is no different than authorship analysis used in digital forensics, a field that shows fairly high accuracy under similar conditions.