Browsing by Subject "Generative Design"

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    Investigating Consumer Responses to AI- versus Human-Designed Fashion Products: A Mind Perception Theory Perspective
    (2023-05) Lee, Garim
    Generative AI, which creates original content based on input data, is becoming prevalent in the consumer environment. The fashion industry can benefit from generative AI, making the overall product design process more efficient and cost and time effective. However, not many studies have investigated how consumers evaluate AI-designed fashion products. The theorization of how consumers perceive AI in the fashion design process is also not yet sufficient. Building on mind perception theory, this study aims to fill the research gaps by examining how consumers evaluate AI’s mental and intentional abilities and respond to AI-designed versus human-designed fashion products.Consumers’ negative bias toward AI-designed (vs. human-designed) fashion products is confirmed across the two online experiments (Study 1: n=289; Study 2: n=289). Such effects are explained by perceived experience, perceived agency, and perceived design expertise, while the roles of perceived agency and design expertise are especially prominent. The advantageous effects of humans over AI as design entity are generally confirmed across different product types in the same product categories and perceived threats from AI. Finally, incorporating human aspects when introducing products designed through AI-assisted processes alleviates consumers’ negative responses. Varying levels of human aspects in AI applications (AI vs. humanized AI designer vs. human-AI collaboration) lead to different ratings between mind perception, perceived design expertise, and consumer responses. The study contributes to the understanding of the applications of generative AI in retail, focusing on the fashion design process. The theoretical and practical implications are provided drawn from the study findings.