IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2023i1p65-d1304154.html
   My bibliography  Save this article

From Image to Imagination: Exploring the Impact of Generative AI on Cultural Translation in Jewelry Design

Author

Listed:
  • Yanru Lyu

    (Department of Digital Media Arts, School of Design and Arts, Beijing Technology and Business University, Beijing 102488, China
    Key Laboratory of Encyclopedia Knowledge Fusion Innovation Publishing Project, Beijing 100037, China)

  • Minghong Shi

    (School of Design and Innovation, Shenzhen Technology University, Shenzhen 518118, China)

  • Yanbo Zhang

    (Department of Textile, Apparel Design and Merchandizing, Louisiana State University, Baton Rouge, LA 70803, USA)

  • Rungtai Lin

    (Graduate School of Creative Industry Design, National Taiwan University of Arts, New Taipei 220307, Taiwan)

Abstract

The current proliferation of artificial intelligence (AI) is prominently shaping the design industry. Generative AI, such as text-to-image and image-to-image models, has gained widespread use, notably for its efficiency and quality improvements. However, their potential to aid in cultural translation within creative design is underexplored. To address the existing gap, this study aims to assess the impact of generative AI on cultural translation within jewelry design. Specifically, a comprehensive study was conducted through a design-action experiment, collecting 46 student designers’ design-action data and self-reports, and enlisting the evaluation from 30 design experts. The findings highlight the substantial influence of generative AI on the ideation phase of jewelry design, especially in depth rather than breadth, and in the shape factor at the technical level such as detailization and unexpected composition. Leveraging AI image generators has shifted the designer’s focus from technical tasks to strategic decisions related to visual appeal, cognitive engagement, and emotional resonance. Furthermore, the challenges inherent in human–AI collaboration have been revealed, stemming from communication difficulties and the risk of fixating on specific details to stylistic constraints. Based on data analysis, a novel hybrid model regarding human–AI co-creation on cultural translation in jewelry design is proposed. Overall, this current study offers a valuable reference point to future research in terms of examining the effect of emerging technologies on cultural translation in creative fields.

Suggested Citation

  • Yanru Lyu & Minghong Shi & Yanbo Zhang & Rungtai Lin, 2023. "From Image to Imagination: Exploring the Impact of Generative AI on Cultural Translation in Jewelry Design," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
  • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:65-:d:1304154
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/1/65/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/1/65/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:65-:d:1304154. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.