A Comparative Study on the Impact of AIGC and Traditional Inspiration Sources on the Design Process of Designers
Open Access
Article
Conference Proceedings
Authors: Yulu Yang, Ruoxuan Ma, Yi Xiao
Abstract: This research delves into the impact of artificial intelligence generated content (AIGC) as a source of inspiration on the ideation process of designers. The study aims to juxtapose the efficacy of designers employing AIGC tools, exemplified by Midjourney, against traditional search engines such as Pinterest during the ideation phase, emphasizing the stages of keyword definition, inspiration search, and inspiration selection. Utilizing think-aloud protocol analysis and semi-structured interviews, the research scrutinized the ideation processes of 12 master's students in design under various task constraints. The outcomes indicated that designers employing AIGC tools demonstrated heightened prudence during the keyword definition phase, and their search depth and selection strategies varied significantly. AIGC tools were found to be more effective in managing associative creative searches, yielding unique design solutions. The study demonstrates that AIGC, as an emerging source of inspiration, possesses certain advantages and potential, showcasing its efficacy as an inspirational source in the early stages of the design process. Additionally, the study offers recommendations for designers on integrating both AIGC and traditional inspiration sources in their creative endeavors.
Keywords: Artificial Intelligence Generated Content, Inspiration Acquisition, Sources of Inspiration, Design Thinking
DOI: 10.54941/ahfe1006116
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