Is AI image generation a creative or optimize tool in product design process?—The usage of AI image generation tools for vehicle shape as an example

Yu-Hsu Lee

Article ID: 8867
Vol 9, Issue 1, 2025


Abstract


This study explores the shape thinking processes and decision-making factors of designers when using AI image generation tools for conceptualizing the shapes of two-wheeled vehicles through four design tasks. Eight designers were invited to create hand-drawn sketches based on a specific aesthetic direction (technological geometry), followed by a shape divergence exercise using two AI graphics tools, Stable Diffusion and Vizcom, to generate images from text prompts. After selecting the designs closest to their original concepts and their favorite designs, the designers used an iPad to explore different shape directions (technological biology) for partial shape modifications. Finally, retrospective interviews were conducted to understand whether there were differences in designers’ thinking process regarding the use of various AI tools for shape conceptualization, as well as their focal points regarding design modification and shape thinking at different stages of the process. The research findings indicate that current AI tools are more suitable for shape divergence. If designers wish to achieve shape convergence, they need to be more familiar with the various settings of AI image generation tools and understand which prompts significantly influence specific shape characteristics. Designers’ perceptions of shape modification primarily revolve around: 1. Outline contours, 2. Parting lines, 3. Variations in surface curvature, and 4. The resulting features (light and shadow effects). Furthermore, it is recommended that future AI image generation tools, if developed as professional assistive tools for product design, should provide two modes—shape divergence and convergence—focusing on both the main shape and details. Additionally, it is suggested that developing AI-3D technologies should address the four key aspects of shape manipulation presented in this study, offering adjustments for overall appearance and detailing the contour lines of parts, including the manipulation of surface curvature and shape positioning.

Keywords


artificial intelligence; image generation; design process; vehicle shape design; motorcycle design

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DOI: https://doi.org/10.24294/jipd8867

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