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International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

A Critical Analysis of the Reliability of Generative Models in Preserving Cultural Privacy: Towards Sustainable Digital Fashion Design Using Artificial Intelligence

Suad Abdullah AlGhamdi, Nermeen Abdelrahman Abdelbaset Mohamed

http://dx.doi.org/10.6007/IJARBSS/v15-i5/25480

Open access

This study aims to analyze the reliability of generative AI models in representing cultural privacy within the field of digital fashion design. A generative model was developed using a curated Saudi heritage database and tested on over fifty generated designs. The study adopted an applied evaluative methodology using an integrated toolset: a technical assessment by experts and a visual questionnaire for designers and specialists. Results indicated that identity-informed designs significantly outperformed non-informed ones in terms of cultural representation, attractiveness, wearability, and clarity of inspiration. Findings also confirmed that integrating heritage data substantially enhances the quality of visual outputs. The study presents a practical model for embedding cultural sensitivity into design algorithms and recommends the adoption of this methodology in other cultural contexts.

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AlGhamdi, S. A., & Mohamed, N. A. A. (2025). A Critical Analysis of the Reliability of Generative Models in Preserving Cultural Privacy: Towards Sustainable Digital Fashion Design Using Artificial Intelligence. International Journal of Academic Research in Business and Social Sciences, 15(5), 1164–1176.