Advances in Generative AI (GenAI) enable unexpected creation in visual images. In fashion design, this capability has intensified demand for creativity support tools where fast-paced trends challenge fixation and drive exploration of novel creative directions. While prior work has explored interfaces that align designer intent with GenAI outputs, we still lack an empirical understanding of how fashion designers define, seek, and utilize AI-generated surprise as a valuable resource and actionable design direction rather than random noise. We address this gap through a qualitative study combining semi-structured interviews with 20 fashion professionals and a design workshop with 12 graduate students. We conceptualized surprise as a strategy that can be designed into GenAI-powered visualization tools to support traceable exploration, contextual grounding, and controllable variation across ideation stages. This work (1) reframes surprise as a designable mechanism or resource for co-creative interaction, (2) provides empirical insights into how fashion designers can utilize AI-generated surprise in the early stage of design, and (3) translates these insights into actionable guidance for building GenAI-driven visualization tools for fashion and related creative domains from a human-centered AI perspective.
ACM CHI Conference on Human Factors in Computing Systems