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Fediverse
Yeah, I don’t think that there’s going to be a viable future in distinguishing between LLM and human text either, certainly not for people who have an interest in defeating it. That being said:
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Some people are just going to use the most-common models.
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Some models are derived from other models and will share statistical similarities.
I still think that trying to detect LLMs is largely going to be a dead-end road, though.
There are also other wrinkles. I’d bet that an increasing amount of not-trying-to-maliciously-impersonate-a-human text out there is going to come from LLMs. Like, okay, Google Translate uses an LLM. I remember listening to an interview with a senior British EU translator (this was back before Brexit). This is going to be a quality human translator. He was saying that machine translation had gotten so good that these days, that now he always did his first pass with Google Translate and just cleaned it up by hand. Okay, so you figure that this is probably widespread, probably even more so now, right? So if most of the EU’s documents are coming from an LLM, even if you could hypothetically detect all LLMs, you probably wouldn’t want to trigger on some of them.
Not to mention that people adopt mannerisms from text that they read or hear spoken. If someone is using, say, automated browser translations, they’re seeing a lot of the world through an LLM, and you’d expect them to pick up characteristics of that.