提出双模式协作框架，引导人机共创中发散与收敛思维的切换。
Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models
- 设计双模式系统：发散探索远程概念，收敛聚焦细节优化。
- 24人实验显示，新系统在创意与可用性上均优于ChatGPT。
- 适合需要深度创意设计的用户，如海报、视觉创作场景。
生成式AI降低了内容创作门槛，但主流聊天界面常直接输出完整结果，导致过早收敛和设计固化。现有探索性接口多受限于初始任务语义范围，抑制创意多样性。本文基于创造性认知的Geneplore模型，构建人机协同创作系统HAICo，将创作过程分为可切换的发散（DIVERGENT）与收敛（CONVERGENT）模式：前者支持远距离概念探索，后者聚焦选定想法的精细优化。在24名用户的海报创作任务中，对比实验表明，HAICo在多个创意维度和可用性指标上均优于ChatGPT。结果强调需从纯执行导向的聊天机器人转向主动引导探索的结构化协同系统。
原文摘要 · Abstract (English)
Generative AI has democratized content creation, but popular chatbot-based interfaces often prioritize execution, generating fully rendered artifacts right away. This issue can lead to premature convergence and design fixation, where users are being anchored to initial outputs. Recent works have proposed new interfaces to address this issue by supporting exploration, though typically constrained to be semantically close to a user's initial task framing, potentially limiting the creativity of the outcomes. We examine an approach grounded in the Geneplore model of creative cognition and instantiate it in a human-AI co-creation system, HAICo, for creative image generation. HAICo explicitly structures the creative process into two switchable modes: DIVERGENT mode scaffolds the broad exploration of remote conceptual ideas; CONVERGENT mode supports a targeted refinement of selected ideas. Through a within-subjects study (N=24) on a poster image creation task, we demonstrate that HAICo outperforms ChatGPT across multiple dimensions of creativity and usability. Our results highlight the critical need to shift from pure execution-focused chatbots to scaffolded co-creation systems that actively guide exploration and foster the creative process.
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