Large language models (LLMs) show strong potential to support creative tasks, but the role of the interface design is poorly understood. In particular, the effect of different modes of collaboration between humans and LLMs on co-creation outcomes is unclear. To test this, we conducted a randomized controlled experiment ($N = 486$) comparing: (a) two variants of reflective, human-led modes in which the LLM elicits elaboration through suggestions or questions, against (b) a proactive, model-led mode in which the LLM independently rewrites ideas. By assessing the effects on idea quality, diversity, and perceived ownership, we found that the model-led mode substantially improved idea quality but reduced idea diversity and users' perceived idea ownership. The reflective, human-led mode also improved idea quality, yet while preserving diversity and ownership. We independently validated the findings in a different context ($N = 640$). Our findings highlight the importance of designing interactions with generative AI systems as reflective thought partners that complement human strengths and augment creative processes.

翻译：大型语言模型（LLM）在支持创造性任务方面展现出巨大潜力，但其界面设计的作用尚未得到充分理解。特别是，人类与LLM之间不同的协作模式对协同创作成果的影响尚不明确。为探究此问题，我们开展了一项随机对照实验（$N = 486$），比较了以下两种模式：（a）两种反思性、人类主导的协作模式变体，其中LLM通过建议或提问引导用户深入阐述；与（b）一种主动性、模型主导的模式，其中LLM独立改写创意。通过评估其对创意质量、多样性及用户感知创意所有权的影响，我们发现模型主导模式显著提升了创意质量，但降低了创意多样性及用户对创意的感知所有权。反思性、人类主导的模式同样提升了创意质量，同时保持了多样性与所有权。我们在另一情境下（$N = 640$）独立验证了这些发现。我们的研究结果强调了将生成式AI系统设计为反思性思维伙伴的重要性，以互补人类优势并增强创作过程。