I’m just guessing here, but if you have a way to train your model with the same or similar types of data as the model you are comparing with, then you have a high probability of detecting when the output is similar. To put it another way, if I ask chatGPT its favorite red condiment and it answers “mustard”, then if my model is trained to give the same answer it makes it easy to detect something that was likely created by an AI. If the answer doesn’t match what my model spits out, then it has a higher chance of being human-generated. Does that make sense?
Yeah that makes sense. I’m still very sceptical though because as your example illustrates, it’s perfectly valid for a human to answer “mustard” as well, plus there is an element of randomness inserted into the model output. Maybe it’s doable but I’m unconvinced that you can meaningfully distinguish between human and AI written text. Unless you make a detector that looks for “As a large language model…” Then maybe it can detect ChatGPT specifically.
Agreed, even a perfectly trained clone of chatGPT wouldn’t get that high a hit rate, although I do think that the larger the article being compared, the better its chances would be of making an accurate prediction. The thing is that we soon won’t actually be able to tell the difference as computers get smarter. Sees like right now the only practical application is for kids to cheat on their homework, but what happens when it gets smart enough to write actual research papers with unique proofs?
If it writes research papers, that research still has to come from somewhere. Even if the whole study was performed by AI itself, how would that deligitimise the research? Science isn’t art, it’s irrelevant who the performing agent is. (As long as it’s not stolen)
I’m just guessing here, but if you have a way to train your model with the same or similar types of data as the model you are comparing with, then you have a high probability of detecting when the output is similar. To put it another way, if I ask chatGPT its favorite red condiment and it answers “mustard”, then if my model is trained to give the same answer it makes it easy to detect something that was likely created by an AI. If the answer doesn’t match what my model spits out, then it has a higher chance of being human-generated. Does that make sense?
Yeah that makes sense. I’m still very sceptical though because as your example illustrates, it’s perfectly valid for a human to answer “mustard” as well, plus there is an element of randomness inserted into the model output. Maybe it’s doable but I’m unconvinced that you can meaningfully distinguish between human and AI written text. Unless you make a detector that looks for “As a large language model…” Then maybe it can detect ChatGPT specifically.
Agreed, even a perfectly trained clone of chatGPT wouldn’t get that high a hit rate, although I do think that the larger the article being compared, the better its chances would be of making an accurate prediction. The thing is that we soon won’t actually be able to tell the difference as computers get smarter. Sees like right now the only practical application is for kids to cheat on their homework, but what happens when it gets smart enough to write actual research papers with unique proofs?
If it writes research papers, that research still has to come from somewhere. Even if the whole study was performed by AI itself, how would that deligitimise the research? Science isn’t art, it’s irrelevant who the performing agent is. (As long as it’s not stolen)