The growing availability of generative AI technologies such as large language models (LLMs) has significant implications for creative work. This paper explores twofold aspects of integrating LLMs into the creative process - the divergence stage of idea generation, and the convergence stage of evaluation and selection of ideas. We devised a collaborative group-AI Brainwriting ideation framework, which incorporated an LLM as an enhancement into the group ideation process, and evaluated the idea generation process and the resulted solution space. To assess the potential of using LLMs in the idea evaluation process, we design an evaluation engine and compared it to idea ratings assigned by three expert and six novice evaluators. Our findings suggest that integrating LLM in Brainwriting could enhance both the ideation process and its outcome. We also provide evidence that LLMs can support idea evaluation. We conclude by discussing implications for HCI education and practice.

翻译：生成式AI技术（如大语言模型）的日益普及对创造性工作产生了深远影响。本文探索将大语言模型融入创造过程的两个层面——发散阶段（创意生成）与收敛阶段（创意评估与筛选）。我们设计了一种人机协作的群体-AI脑力书写构思框架，将大语言模型作为增强手段融入群体构思过程，并对创意生成流程及最终方案空间进行了评估。为考察大语言模型在创意评估中的潜力，我们构建了一个评估引擎，并将其与三位专家及六位新手评估员给出的评分进行比较。研究结果表明，将大语言模型嵌入脑力书写法既能优化构思过程，也能提升最终成果质量。此外，我们提供了大语言模型可辅助创意评估的证据。最后，我们讨论了相关发现对人机交互教育与实践的启示。