This study examines the role of vagueness in the design process and its strategic management for the effective human-AI interaction. While vagueness in the generation of design ideas promotes diverse interpretations and prevents fixation, excessive vagueness can lead to scattered results. Designers attempt to use image search tools or generative AIs (e.g., Dall-E) for their work but often fail to achieve satisfactory results because the level of vagueness is not properly managed in these technologies. In this work, we identified how designers coordinate vagueness in their design process and applied key components of the process to the design of CLAY, an interactive system that balances vagueness through iterative prompt refinement by integrating the strengths of text-to-image generative AI. Results from our user study with 10 fashion designers showed that CLAY effectively supported their design process, reducing design time, and expanding creative possibilities compared to their existing practice, by allowing them to both embrace and avoid vagueness as needed. Our study highlights the importance of identifying key characteristics of the target user and domain, and exploring ways to incorporate them into the design of an AI-based interactive tool.

翻译：本研究探讨了模糊性在设计过程中的作用及其在人机交互中的策略性管理。设计创意生成过程中的模糊性虽能促进多元解读并避免思维定势，但过度模糊会导致结果分散。设计师尝试使用图像搜索工具或生成式人工智能（如Dall-E）进行创作，但由于这些技术未能妥善管理模糊程度，往往难以获得满意结果。本工作通过分析设计师如何在设计过程中协调模糊性，将其关键流程要素应用于CLAY系统的设计——这是一个通过整合文本到图像生成式人工智能优势，借助迭代式提示词优化来实现模糊性平衡的交互系统。我们对10位时装设计师开展的用户研究表明，与现有设计实践相比，CLAY系统能有效支持设计流程，通过允许设计师根据需要灵活把握或规避模糊性，显著缩短设计时间并拓展创意可能性。本研究强调，在基于人工智能的交互工具设计中，识别目标用户与领域的关键特征并将其融入系统设计至关重要。