From Paper to Card: Transforming Design Implications with Generative AI
Donghoon Shin Lucy Lu Wang Gary Hsieh
Communicating design implications is common within the HCI community when
publishing academic papers, yet these papers are rarely read and used by
designers. One solution is to use design cards as a form of translational
resource that communicates valuable insights from papers in a more digestible
and accessible format to assist in design processes. However, creating design
cards can be time-consuming, and authors may lack the resources/know-how to
produce cards. Through an iterative design process, we built a system that
helps create design cards from academic papers using an LLM and text-to-image
model. Our evaluation with designers (N=21) and authors of selected papers
(N=12) revealed that designers perceived the design implications from our
design cards as more inspiring and generative, compared to reading original
paper texts, and the authors viewed our system as an effective way of
communicating their design implications. We also propose future enhancements
for AI-generated design cards.