Detection methods only serve to stop the most blatant, low effort kind of LLM responses. The more pressing issue is that people are reading LLM output, and paraphrasing it for their assignments, reports, emails, etc. The obvious problem being that LLMs are often wrong, or miss nuance in unnoticeable ways for the laymen. The secondary problem is the general outsourcing of thinking and effort, even for tasks that you ought to give your focus to. BTW: from my anecdata, most university students are absolutely violating academic integrity with these tools, and have completely lost the ability to engage without them.
This is an article from 2024, when open weights models like llama were only beginning to emerge. With those you basically cannot reliably do any detection (as the authors admit by the end).
Which is really boiling down to text having statistically very similar properties to human generated one. Introduce a more motivated attacker and the text would be indistinguishable from real (with occasional typos, no use of "delve", "it's not x its y", emdashes and so on).
It really is a lost battle: you cannot embed extra information in the text that will survive even basic postprocessing (in contrast to, say, steganography)
I see a lot of people claiming just about everything is AI these days, including totally normal videos, photos and text. I'm not sure what the solution will be to this phenomena but we're in for a bit of trouble for a while.
Detection methods only serve to stop the most blatant, low effort kind of LLM responses. The more pressing issue is that people are reading LLM output, and paraphrasing it for their assignments, reports, emails, etc. The obvious problem being that LLMs are often wrong, or miss nuance in unnoticeable ways for the laymen. The secondary problem is the general outsourcing of thinking and effort, even for tasks that you ought to give your focus to. BTW: from my anecdata, most university students are absolutely violating academic integrity with these tools, and have completely lost the ability to engage without them.
This is an article from 2024, when open weights models like llama were only beginning to emerge. With those you basically cannot reliably do any detection (as the authors admit by the end).
Which is really boiling down to text having statistically very similar properties to human generated one. Introduce a more motivated attacker and the text would be indistinguishable from real (with occasional typos, no use of "delve", "it's not x its y", emdashes and so on).
It really is a lost battle: you cannot embed extra information in the text that will survive even basic postprocessing (in contrast to, say, steganography)
It sounds like a "cursed problem". Are there any contemporary techniques that show any promise?
I see a lot of people claiming just about everything is AI these days, including totally normal videos, photos and text. I'm not sure what the solution will be to this phenomena but we're in for a bit of trouble for a while.