  Large language models (LLMs) are now being used in a wide variety of
contexts, including as creativity support tools (CSTs) intended to help their
users come up with new ideas. But do LLMs actually support user creativity? We
hypothesized that the use of an LLM as a CST might make the LLM's users feel
more creative, and even broaden the range of ideas suggested by each individual
user, but also homogenize the ideas suggested by different users. We conducted
a 36-participant comparative user study and found, in accordance with the
homogenization hypothesis, that different users tended to produce less
semantically distinct ideas with ChatGPT than with an alternative CST.
Additionally, ChatGPT users generated a greater number of more detailed ideas,
but felt less responsible for the ideas they generated. We discuss potential
implications of these findings for users, designers, and developers of
LLM-based CSTs.
