DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design
For novice product designers, this work addresses the challenge of exploring design spaces without expert domain knowledge, but the results are incremental and highlight limitations of current AI.
DesignWeaver helps novice product designers generate better prompts for text-to-image AI by surfacing key design dimensions from generated images, leading to more diverse and innovative designs, though it also raises expectations beyond current model capabilities.
Generative AI has enabled novice designers to quickly create professional-looking visual representations for product concepts. However, novices have limited domain knowledge that could constrain their ability to write prompts that effectively explore a product design space. To understand how experts explore and communicate about design spaces, we conducted a formative study with 12 experienced product designers and found that experts -- and their less-versed clients -- often use visual references to guide co-design discussions rather than written descriptions. These insights inspired DesignWeaver, an interface that helps novices generate prompts for a text-to-image model by surfacing key product design dimensions from generated images into a palette for quick selection. In a study with 52 novices, DesignWeaver enabled participants to craft longer prompts with more domain-specific vocabularies, resulting in more diverse, innovative product designs. However, the nuanced prompts heightened participants' expectations beyond what current text-to-image models could deliver. We discuss implications for AI-based product design support tools.