StoryDiffusion: How to Support UX Storyboarding With Generative-AI

TL;DR

This paper introduces StoryDiffusion, an AI-powered system that integrates narrative and image generation to enhance UX storyboarding, addressing the need for supporting the entire creative process in design workflows.

Contribution

The work presents a novel integrated AI system supporting both narrative and visual creation in UX storyboarding, with insights from user studies on designer strategies and preferences.

Findings

AI-directed and user-directed creative strategies identified

Interchange between narrative iteration and image generation is crucial

Design tasks influence designer strategies and preferences

Abstract

Storyboarding is an established method for designing user experiences. Generative AI can support this process by helping designers quickly create visual narratives. However, existing tools only focus on accurate text-to-image generation. Currently, it is not clear how to effectively support the entire creative process of storyboarding and how to develop AI-powered tools to support designers' individual workflows. In this work, we iteratively developed and implemented StoryDiffusion, a system that integrates text-to-text and text-to-image models, to support the generation of narratives and images in a single pipeline. With a user study, we observed 12 UX designers using the system for both concept ideation and illustration tasks. Our findings identified AI-directed vs. user-directed creative strategies in both tasks and revealed the importance of supporting the interchange between narrative iteration and image generation. We also found effects of the design tasks on their strategies and preferences, providing insights for future development.