| Principle | Recommendation | |-----------|----------------| | Transparency | Label all AI-generated images with visible metadata and captions. | | Bias auditing | Regularly test prompts for racial, size, age, and gender diversity. | | Data consent | Only train on openly licensed or in‑house fashion datasets. | | No impersonation | Do not generate fake models mimicking real influencers or celebrities. | | Environmental impact | Use efficient local models rather than cloud‑heavy generation. |
These are original photoshoots created by fans using photo manipulation software. A fan might shoot a friend in a vintage coat, then edit Kim Tae’s face and signature mole onto the image, adjusting skin tones to match the "mood" of a Gucci or Celine campaign. fake kim tae hee nude photo updated
This paper examines the emergence of “Fake Kim Tae”—a hypothetical AI-generated fashion photoshoot and style gallery featuring a non-existent model. Through synthetic media production, the project interrogates authenticity, authorship, and representation in contemporary fashion imaging. Using generative AI tools (Midjourney, DALL‑E 3, and Stable Diffusion), we constructed a 25-look style gallery that mimics the visual language of high-fashion editorials (e.g., Vogue Korea, Numéro). The paper analyzes how AI perpetuates or disrupts conventional beauty standards, body ideals, and cultural signifiers. Findings suggest that while synthetic models allow for radical creative freedom, they also risk homogenizing aesthetics and eroding trust in fashion documentation. We propose the concept of the synthetic style gallery as a new genre requiring transparent labeling and critical curation. The paper concludes with ethical guidelines for AI-assisted fashion photography. These are original photoshoots created by fans using