alt Hacker NewsText is simply not information dense enough to be able to decode some arbitrary signal of provenance from it. Sure you might be able to detect today's tells (particular sentence structures preferred by Claude, phrases, etc) to get you some arbitrary chance percentage it was machine generated, but it's a bad fiction to perpetuate that any of this is anything more than tarot card reading.
Images, absolutely, there are tell-tale artifacts from today's generators that simply aren't emitted by "natural" paths to create them, and you can "detect AI" with high confidence (for now). Words, no, the signal is far too sparse and we are well into undetectable sophistication with today's models, let alone tomorrow's.
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There are two problems, false positives and changing the LLM's pattern.
It's really easy to have a false positive and false positives can be very harmful if the person using the detector isn't aware of that risk.
It's also very easy to change the pattern of LLM output. You can provide basic prompting that will significantly change the structure of the output. For example, having it utilize the Wikipedia article on signs of AI writing and avoid everything it describes. https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
Signal is easier to detect with more data to work with.
Largely AI generated books are a vastly different situation than a one paragraph homework assignment. But multiple rounds of homework assignments would change the accuracy.
"Text is simply not information dense enough to be able to decode some arbitrary signal of provenance from it...it's a bad fiction to perpetuate that any of this is anything more than tarot card reading."
Not true at all. Pangram is highly effective and has a very low false positive rate.
The post here is impressive for a small project, it looks like they independently thought of one of the core ideas Pangram uses of creating twins to compare.
You can see how it works here: https://arxiv.org/pdf/2402.14873
> but it's a bad fiction to perpetuate that any of this is anything more than tarot card reading.
Hard disagree. LLMs (especially base ones, that only received pre-training) can produce output that is undistinguishable from human writing (because that's what they were trained to do).
But commercial chat models are specifically tuned in a way that maximizes user engagement. It's that specific tuning that is very easy to spot when reading AI slop, and that's not surprising that it's easy to spot automatically either. And I don't think that's going to change anytime soon, unless their incentives change.
(We can say exactly the same thing about man-made stuff optimized for a specific purpose, like stock photography, clickbait titles or industrial food: they aren't stereotypical because their creator lacks the skill to make them otherwise, they are like that because that's what works best).
I don't know, the thing about most text slop is how little effort goes into disguising it (for now, anyway). I'm sure anyone dedicated can go undetected, but it's the really low-effort stuff that's generally the problem. If you can catch some of it, that's something at least.
i think one thing overlooked by this perspective is that many of a detectors adversaries are not that sophisticated. so despite this i think it is a useful thing to try to do. particularly when people are trying to do fraud which will often having to use abliterated models and generally trying to be as economical in their efforts
This sounds like it was edited by an llm.
Sure it is; we do it all the time, and then we modify each other's etc, etc; english we speak today was spoke yesterday waspake the same in yesteryears; we have no trouble dating english or other languages to a time.
A better argument is people themselves are just too influenced by reading that they'll sound like LLMs in a couple of years.
It depends on how much text. For example, chardet often falls down on short strings, but 1K characters it nails it.
The best method is, as always, an anti-privacy method.
Simply track all citizens' writing patterns throughout their life, from cradle to grave, then diff with any given text's signature--you'll know if it was human written or not.
Better--opt in--install a "personal text signature" on your devices, sign things that you wrote yourself with it.
But I suppose that's just like the image provenance chips on cameras.
Either way father fascism is more with us than ever, praise him!
Whether a text was written by a human or not is just a single bit of information. So you can't rule out its detectability a priori, since even the shortest text contains more information than that.
As long as LLMs are used to write texts humans wouldn't want to write if they could help it (that's why they're getting an LLM to do it, after all), they'll remain detectable. Even if the reasoning might end up equivalent to "This looks like spam; no human in their right mind would write this spam by hand if they could get an LLM to write it, therefore it's most likely written by an LLM."