创造力
感知
工程设计过程
任务(项目管理)
服装设计
心理学
过程(计算)
设计教育
相似性(几何)
构思
创意技巧
计算机科学
知识管理
人工智能
人机交互
工业设计
认知心理学
空格(标点符号)
社会心理学
工程类
研究设计
工作设计
设计过程
余弦相似度
收敛性思维
任务分析
作者
Elisa Koolman,George Moore,Lena Young,Eric Reynolds Brubaker,Anastasia M. K. Schauer
摘要
Abstract Engineering future worlds in a speculative design process requires creative ideas. Speculative design has ties to both engineering design and creative writing, and while artificial intelligence (AI) use has been found to impact the creativity of ideas in both domains, these fields have conflicting findings related to the impact of AI on idea novelty. Through a study of three groups of professional engineers and designers, we explore the relationships between dimensions of creativity and perceptions of creativity across different AI usage conditions during speculative design in a professional setting. Experts and designers assessed 120 ideas that were either fully human-generated, generated by humans using AI-as-tool, or fully AI-generated. In this context, AI use improved the well-craftedness and usefulness of ideas with no significant impact on novelty, although cosine similarity indicated that AI-generated ideas explored a smaller design space than the other conditions. Designers rated AI-generated ideas as less well-crafted and useful than experts, which may be indicative of ownership bias or “human favoritism” by the participants in this study. Additionally, designers who did not use AI displayed higher creative self-confidence, assessing their ideas as more well-crafted, novel, and useful compared to designers who used AI-as-tool. Overall findings indicate that AI use impacted various dimensions of creativity within this speculative design sprint, and while designer ratings often align with experts, perceptions of creativity can be biased by awareness of AI use. The inconsistent findings observed in both prior literature and our groups of designer groups regarding AI use and creativity highlight the need for continued investigation into how AI use affects design outcomes across different tasks and contexts.
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