The effect of AI-based inspiration on human design ideation
Jingoog Kim, Mary Lou Maher
Abstract
Computational co-creative systems in design allow users to collaborate with an AI partner on open-ended creative tasks in the design process. Co-creative systems can enhance design creativity by inspiring the exploration of novel design solutions in the initial idea generation. However, there are a lack of studies about the effect of co-creative systems on the cognitive process during ideation. This study examines the effect of an AI-based co-creative design tool that provides inspirations based on conceptual similarity on design ideation. It was hypothesized that conceptually similar inspirations have a significant influence on design ideation than random inspirations. The Collaborative Ideation Partner (CIP), a co-creative design system that provides inspirational images based on conceptual similarity, was developed to examine the effect of an AI Model for conceptual similarity on ideation during a design task. We conducted an experiment with a control condition in which the images are selected randomly from a curated database for inspiration and a treatment condition in which conceptual similarity is the basis for selecting the next inspiring image. Our findings show that the AI model of conceptual similarity used in the treatment condition has a significant effect on the novelty, variety, and quantity of ideas during human design ideation.