IMPACT OF AI ON PHOTOGRAPHY: REDEFINING CREATIVITY AND AUTHORSHIP

Abstract

This study provides an in-depth exploration of Generative Adversarial Networks (GANs) and their
transformative impact on digital art, covering areas such as photography, painting, and creative reanimation
[1]. By utilizing GAN architectures, the research delved into how synthetic images are generated, refined, and
integrated into various artistic workflows. The study highlights GANs' ability to replicate human artistry
through iterative training and real-time adjustments, challenging traditional notions of creativity and reshaping
the digital art landscape. However, despite their potential to produce realistic and unique artworks, GANs face
significant challenges. Key issues include the need for diverse, high-quality datasets, hardware limitations, and
the subjective nature of assessing realism. Moreover, GANs struggle to understand human intent and the
conceptual depth of art, which restricts their ability to fully engage in creative processes. The
commercialization of AI-generated art, particularly through digital platforms and NFTs, raises complex
questions about authorship, originality, and the essence of creativity. As AI continues to shape art creation,
defining clear intellectual property frameworks will be essential to navigate these challenges [2]. Despite these
obstacles, GANs offer exciting opportunities for artists and the broader creative industry, fostering new forms of
expression and artistic experimentation in the evolving landscape of digital art.