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）现已被广泛应用于多种场景，包括作为旨在帮助用户产生新想法的创意支持工具（CSTs）。然而，LLMs是否真正支持了用户的创造力？我们假设，将LLM作为CST使用可能会让用户感到更具创造力，甚至能拓宽单个用户提出的想法范围，但同时也会使不同用户提出的想法趋于同质化。我们进行了一项36名参与者的对比用户研究，结果发现，与替代性CST相比，使用ChatGPT的不同用户倾向于产生语义上更不独特的想法，这与同质化假设一致。此外，ChatGPT用户生成了更多、更详细的想法，但对自己产生的想法责任感较低。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影响。