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：生成式人工智能技术（如大语言模型）的日益普及对创造性工作产生了重要影响。本文从两个维度探究将大语言模型整合到创意过程中的应用——创意生成的发散阶段，以及创意评估与筛选的收敛阶段。我们设计了一个协作式群体-人工智能脑力书写创意生成框架，将大语言模型作为增强工具融入群体创意过程，并对创意生成过程及最终解决方案空间进行了评估。为评估大语言模型在创意评价过程中的潜力，我们构建了一个评价引擎，并将其与三位专家与六位新手评价者给出的创意评分进行了比较。研究结果表明，将大语言模型整合到脑力书写中既能优化创意生成过程，也能提升创意成果质量。同时，我们还提供了大语言模型可支持创意评价的实证证据。最后，本文讨论了该研究对人机交互教育与实践的启示意义。