DesignBridge: Bridging Designer Expertise and User Preferences through AI-Enhanced Co-Design for Fashion

2026-01-21

AI Summary

This study addresses the challenge in traditional fashion design of reconciling professional creative intent with users’ authentic preferences, which often results in low user engagement and inefficient preference elicitation. To bridge this gap, the authors propose a three-stage AI-augmented co-design system: designers first articulate an initial concept; users then express their preferences intuitively through an interactive interface; and an AI module interprets user interaction data, maps it to design semantics, and assists designers in synthesizing feedback into refined final designs. The system introduces a novel multi-platform collaborative framework that preserves expert design judgment while enabling non-expert users to convey preferences effectively, thereby achieving intelligent integration of user input and design decisions. User studies demonstrate that the approach significantly improves both the efficiency of preference collection and the accuracy of analysis, successfully balancing creative vision with user needs.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Knowledge Representation and Reasoning: Preferences
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Economics, Online Markets and Human Computation: Economics and fairness of platforms and recommendation systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Effective collaboration between designers and users is important for fashion design, which can increase the user acceptance of fashion products and thereby create value. However, it remains an enduring challenge, as traditional designer-centric approaches restrict meaningful user participation, while user-driven methods demand design proficiency, often marginalizing professional creative judgment. Current co-design practices, including workshops and AI-assisted frameworks, struggle with low user engagement, inefficient preference collection, and difficulties in balancing user feedback with design considerations. To address these challenges, we conducted a formative study with designers and users experienced in co-design (N=7), identifying critical challenges for current collaboration between designers and users in the co-design process, and their requirements. Informed by these insights, we introduce DesignBridge, a multi-platform AI-enhanced interactive system that bridges designer expertise and user preferences through three stages: (1) Initial Design Framing, where designers define initial concepts. (2) Preference Expression Collection, where users intuitively articulate preferences via interactive tools. (3) Preference-Integrated Design, where designers use AI-assisted analytics to integrate feedback into cohesive designs. A user study demonstrates that DesignBridge significantly enhances user preference collection and analysis, enabling designers to integrate diverse preferences with professional expertise.

Problem

• co-design
• fashion design
• user preferences
• designer expertise
• AI-enhanced collaboration

Innovation

• AI-enhanced co-design
• preference integration
• interactive fashion design
• designer-user collaboration
• intelligent design system