Creativity from Surprise: Bridging the Gap Between Fashion Designers' Inspiration Work and AI Creative Support Tools
Yu Jin, Yousang Kwon, Juhyeok Yoon, Bowen Zhan, Kyungho Lee
Abstract
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.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get ac43f367-77bb-4aa8-977e-afb8fd4ece31Related papers
- Exploring Design Practice with Generative AI: Perspectives from AEC Design ProfessionalsYue Xu, Yi Wang, Weiyue Gao, Yichen Chai et al.CHI 2026 · 1 citation
- FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion DesignYoungseung Jeon, Seungwan Jin, Patrick C. Shih, Kyungsik HanCHI 2021 · 143 citations
- DesignTrace: Exploring, Iterating and Tracking Design Alternatives with GenAIXiaohan Peng, Debanjana Haldar, Wendy E. Mackay, Janin KochCHI 2026 · 3 citations
- GeneyMAP: Exploring the Potential of GenAI to Facilitate Mapping User Journeys for UX DesignYihan Mei, Zhao Wu, Junnan Yu, Wenan Li et al.CHI 2025 · 12 citations
- Fashioning Creative Expertise with Generative AI: Graphical Interfaces for Design Space Exploration Better Support Ideation Than Text PromptsRichard Lee Davis, Thiemo Wambsganss, Wei Jiang, Kevin Gonyop Kim et al.CHI 2024 · 40 citations
