I wanted to check this. So I tracked down the pnas paper from the press release article, and then I tracked down the 32 page arxiv paper from there https://arxi

I wanted to check this. So I tracked down the pnas paper from the press release article, and then I tracked down the 32 page arxiv paper from there https://arxiv.org/abs/2206.07271 https://arxiv.org/abs/2206.07271 and it still doesn't answer this question from my understanding of the paper. Its main point is "In our three main experiments, using two different language models to generate verbal self-presentations across three social contexts, participants identified the source of a self-presentation with only 50 to 52% accuracy." They did clarify that their data sets were constructed to be 50% human and 50% AI generated. But as far as I could tell, in their reported identification accuracy they do break it down by some categories, but they never break it down in a way that you could tell if the 50%-52% is from the participants always guessing it's human or always guessing it's AI or 50% guessing each and still getting it wrong half the time. In figure S2 literally at the very end of the paper they do show a graph that somewhat addresses how the participants guess, but it's for a subsequent study that looks at a related but different thing. It's not a breakdown of the data they got from the 50%-52% study.