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.

翻译：大型语言模型（LLMs）正被广泛应用于各类场景，包括作为旨在帮助用户产生新创意的创造力支持工具（CSTs）。但LLMs是否真正提升了用户的创造力？我们假设：将LLM用作CST可能使用户自我感觉更具创造力，甚至能拓展单个用户所提出想法的范围，但同时也会使不同用户提出的想法趋于同质化。通过一项包含36名参与者的对比用户研究，我们发现，与使用替代性CST相比，使用ChatGPT的用户所提出的想法在语义上更缺乏区分度，这与均质化假说相符。此外，ChatGPT用户虽然能生成数量更多、细节更丰富的想法，但对自己所产生想法的责任感却更低。我们讨论了这些发现对基于LLM的CST的用户、设计者和开发者的潜在启示。