AI-Generated Nostalgic Designs Balancing Authenticity And Innovation In Saudi Heritage Preservation Eco-Friendly Furniture: Aesthetics And Color Trends
Abstract
The present research investigates the potential impact of AI-generated evocative designs on the conservation of Saudi cultural heritage. The purpose of this study is to examine the perspectives of subject matter experts and collect data regarding the advantages and disadvantages of utilizing AI-generated designs in the preservation of cultural heritage. Utilizing interviews and a Likert-scale questionnaire, the research utilized a mixed-methods strategy to collect both qualitative and quantitative data from authorities in the field. The interviews were carried out with experts in the preservation of Saudi cultural heritage, preservationists, architects, and other relevant professionals. The participants engaged in a discourse regarding the ethical implications, the difficulties encountered in heritage preservation, and the function of AI-generated designs. A larger sample of experts was surveyed using a Likert-scale questionnaire in order to collect quantitative data on their perspectives and attitudes concerning the application of AI-generated designs in the field of heritage preservation. The results indicate that designs inspired by nostalgia and generate[1]d by artificial intelligence have the capacity to significantly aid in the conservation of Saudi heritage. The capability of AI to digitally restore and visualize heritage sites, thereby providing visitors with immersive experiences, was recognized by the experts. Furthermore, they acknowledged the potential of designs generated by artificial intelligence in terms of increasing consciousness, stimulating curiosity among younger cohorts, and enabling digital documentation and preservation. Nevertheless, the disadvantages identified by the experts included the potential for an excessive dependence on AI, apprehensions regarding authenticity and integrity, and the possible erosion of traditional craftsmanship.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
CC Attribution-NonCommercial-NoDerivatives 4.0