Portraying Large Language Models as Machines, Tools, or Companions Affects What Mental Capacities People Attribute to Them

How do people determine whether non-human entities have thoughts and feelings — an inner mental life? Prior work has proposed that people use compact sets of dimensions (e.g., body-heart-mind) to form beliefs about familiar kinds, but how do they generalize to novel entities? Here we investigate emerging beliefs about the mental capacities of large language models (LLMs) and how those beliefs are shaped by how LLMs are portrayed. Participants (N = 470) watched brief videos that encouraged them to view LLMs as either machines, tools, or companions then took a survey measuring mental capacity attributions. We found that the companion group more strongly endorsed statements regarding a broad array of mental capacities that LLMs might possess relative to the machine and tool groups, suggesting that people's beliefs can be rapidly shaped by context. Our study highlights the need to explore the factors shaping people's beliefs about emerging technologies to promote accurate public understanding.