FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion Design

要旨

Recent research on creativity support tools (CST) adopts artificial intelligence (AI) that leverages big data and computational capabilities to facilitate creative work. Our work aims to articulate the role of AI in supporting creativity with a case study of an AI-based CST tool in fashion design based on theoretical groundings. We developed AI models by externalizing three cognitive operations (extending, constraining, and blending) that are associated with divergent and convergent thinking. We present FashionQ, an AI-based CST that has three interactive visualization tools (StyleQ, TrendQ, and MergeQ). Through interviews and a user study with 20 fashion design professionals (10 participants for the interviews and 10 for the user study), we demonstrate the effectiveness of FashionQ on facilitating divergent and convergent thinking and identify opportunities and challenges of incorporating AI in the ideation process. Our findings highlight the role and use of AI in each cognitive operation based on professionals’ expertise and suggest future implications of AI-based CST development.

著者
Youngseung Jeon
Ajou University, Suwon, Korea, Republic of
Seungwan Jin
Ajou University, Suwon, Korea, Republic of
Patrick C.. Shih
Indiana University Bloomington, Bloomington, Indiana, United States
Kyungsik Han
Ajou University, Suwon, Korea, Republic of
DOI

10.1145/3411764.3445093

論文URL

https://doi.org/10.1145/3411764.3445093

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Computational Design

[A] Paper Room 02, 2021-05-12 17:00:00~2021-05-12 19:00:00 / [B] Paper Room 02, 2021-05-13 01:00:00~2021-05-13 03:00:00 / [C] Paper Room 02, 2021-05-13 09:00:00~2021-05-13 11:00:00
Paper Room 02
15 件の発表
2021-05-12 17:00:00
2021-05-12 19:00:00
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