Ethical Threads: Exploring Generative Artificial Intelligence in Fashion Education

This study explores the rapidly evolving intersection of artificial intelligence (AI) and fashion, spotlighting the ethical challenges that come with integrating Generative Artificial Intelligence (GAI) into the classroom. As GAI reshapes creative industries, it promises exciting new possibilities— yet also raises pressing questions around bias, ownership, and the future of human-AI collaboration. To address these complexities, this research developed and tested a fashion-focused ethics intervention aimed at preparing students not just to use GAI tools, but to engage with them thoughtfully and responsibly. Through a quasi-experimental mixed-methods design, the study investigated how an ethics lesson influenced students’ perceptions of text- and image-based GAI tools. Results underscore the essential role of ethics education in helping future professionals navigate AI’s challenges with integrity. These insights offer valuable guidance for educators seeking to equip students with both the technical skills and the ethical mindset needed to thrive—and lead—in an AI-driven creative landscape

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Publication Details

Journal
Iowa State University Digital Repository (Iowa State University)
Published
2025-07-30
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
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article

Ethical Threads: Exploring Generative Artificial Intelligence in Fashion Education

Jay Sang Ryu, Rachel Eike, Leslie Browning-Samoni
Iowa State University Digital Repository (Iowa State University)
Generative Adversarial Networks and Image Synthesis
article

Ethical Threads: Exploring Generative Artificial Intelligence in Fashion Education

Jay Sang Ryu, Rachel Eike, Leslie Browning-Samoni
article en

Abstract

This study explores the rapidly evolving intersection of artificial intelligence (AI) and fashion, spotlighting the ethical challenges that come with integrating Generative Artificial Intelligence (GAI) into the classroom. As GAI reshapes creative industries, it promises exciting new possibilities— yet also raises pressing questions around bias, ownership, and the future of human-AI collaboration. To address these complexities, this research developed and tested a fashion-focused ethics intervention aimed at preparing students not just to use GAI tools, but to engage with them thoughtfully and responsibly. Through a quasi-experimental mixed-methods design, the study investigated how an ethics lesson influenced students’ perceptions of text- and image-based GAI tools. Results underscore the essential role of ethics education in helping future professionals navigate AI’s challenges with integrity. These insights offer valuable guidance for educators seeking to equip students with both the technical skills and the ethical mindset needed to thrive—and lead—in an AI-driven creative landscape

Iowa State University Digital Repository (Iowa State University)
Quality Education
Openalex Percentile: Top 25%
Generative Adversarial Networks and Image Synthesis
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