  Advances in AI invite the misuse of language models as stand-ins for human
minds or participants, which fundamentally mischaracterizes these statistical
algorithms. We argue that language models should be embraced as flexible
simulation tools, able to mimic a wide range of behaviors, perspectives, and
psychological attributes evident in human language data, but the models
themselves should not be equated to or anthropomorphized as human minds.
