Interesting angle! We're showing that people fall for generated language not necessarily because generated language is all that good, but because people are loo

Interesting angle! We're showing that people fall for generated language not necessarily because generated language is all that good, but because people are looking for the wrong cues and are thus bad at identifying generated language. Back to the scissors, it would be like someone trying to tell you that their scissors cut marvelously, but you ask yourself whether the paper they are demonstrating them on is strong enough to prove that. Making something for cutting doesn't guarantee that it will cut and doesn't explain why. I even suspect that in the early days of scissors it was all that clear why they worked. Similarly, we don't understand much about GPT-3. It was trained to predict the next token in a sequence, not to create an illusion of personhood. But somehow it does so, and we're trying to understand how and why.