This study examines choice overload and decision-making uncertainty among fashion designers working within generative AI environments and proposes a structured aesthetic judgment model to guide evaluative decision-making. While generative AI has significantly reduced the time and cost required to generate design forms, it has also shifted the designer's role from that of a primary creator to that of a critical evaluator responsible for selecting viable design alternatives from a rapidly expanding set of options. However, existing research on human-AI interaction and collaboration has largely focused on operational efficiency and generative performance, leaving the evaluative criteria, judgment processes, and decision-making logics that guide design selection under explored. To address this gap, this study repositions brand identity not merely as a post hoc management concept, but as a cognitive and aesthetic framework that enables designers to systematically structure selection processes before final design decisions are made. From this perspective, the study proposes a three-stage aesthetic judgment model centered on brand identity. The model comprises (a) cognitive homology alignment, which narrows the decision space by excluding alternatives that conflict with the brand's historically accumulated formal aesthetics; (b) contextual semiotic reconstruction, which interprets design alternatives in relation to the brand's narrative, cultural codes, and symbolic associations; and (c) axiological final validation, which determines whether a design can be formally endorsed as a legitimate expression of the brand’s core values. As a conceptual study grounded in an integrative literature review, this research contributes to the scholarly literature by redefining professional expertise in generative AI-driven fashion design. Specifically, it shifts the focus from the mere production of design outputs to the justification and articulation of aesthetic and brand-centered design decisions.
Yeonyi Jung (Thu,) studied this question.
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