Generative Artificial Intelligence (Generative AI) holds significant promise in reshaping interactive systems design, yet its potential across the four key phases of human-centered design remains underexplored. This article addresses this gap by investigating how Generative AI contributes to requirements elicitation, conceptual design, physical design, and evaluation. Based on empirical findings from a comprehensive eight-week study, we provide detailed empirical accounts and comparisons of successful strategies for diverse design activities across all key phases, along with recurring prompting patterns and challenges faced. Our results demonstrate that Generative AI can successfully support the designer in all key phases, but the generated outcomes require manual quality assessments. Further, our analysis revealed that the successful prompting patterns used to create or evaluate outcomes of design activities require different structures depending on the phase of the design and the specific design activity. We derive implications for designers and future tools that support interaction design with Generative AI.

翻译：生成式人工智能在重塑交互系统设计方面展现出巨大潜力，但其在以人为中心设计四个关键阶段中的应用潜力尚未得到充分探索。本文通过研究生成式人工智能如何辅助需求获取、概念设计、物理设计和评估阶段，填补了这一研究空白。基于为期八周的综合性实证研究结果，我们详细描述了各关键阶段不同设计活动的成功策略案例与比较分析，同时总结了反复出现的提示模式及面临的挑战。研究结果表明，生成式人工智能能够有效支持设计师完成所有关键阶段的工作，但生成结果仍需人工质量评估。进一步分析显示，用于创建或评估设计活动成果的成功提示模式，其结构需根据设计阶段和具体设计活动的特点进行相应调整。本研究为设计师及未来支持生成式人工智能交互设计的工具提出了实践启示。