The effect of AI-based inspiration on human design ideation

构思 概念设计 创造力 相似性(几何) 新颖性 概念模型 过程(计算) 任务(项目管理) 计算机科学 工程设计过程 设计过程 人工智能 心理学 人机交互 工程类 图像(数学) 社会心理学 认知科学 在制品 系统工程 运营管理 机械工程 数据库 操作系统
作者
Jingoog Kim,Mary Lou Maher
出处
期刊:International journal of design creativity and innovation [Informa]
卷期号:11 (2): 81-98 被引量:32
标识
DOI:10.1080/21650349.2023.2167124
摘要

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.
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