Understanding the Differences in an AI-Based Creativity Support Tool Between Creativity Types in Fashion Design

Abstract

As the perspective on creativity shifts to “how it is expressed,” research has aimed to categorize it by problem-solving style. Since harnessing individual creative traits can positively impact creative performance, there has been an emphasis on designing computer systems that are tailored to personal problem-solving behaviors. AI-CST has opened up the potential to facilitate such customization. In this work, we consider two types of creativity—adaptors and innovators—based on problem-solving styles, and investigate AI-CST designs that both types could flexibly use according to the fashion design process. We identified two main AI-CST functions—determining design direction and receiving design inspiration—of the fashion design process, and developed CoCoStyle to map these functions. Through a user study with 30 fashion professionals (15 adaptors and 15 innovators), we found significant differences between the two groups from survey responses, system usage logs, and interviews. Based on the results, we discuss the theoretical and practical implications of AI and AI-CST where creativity is essential.