인공지능과 사진 예술의 융합: 창작 주체성과 법적·윤리적 논의

This study examines the impact of Generative AI technology on photographic art creation, focusing on creative agency and the future of human-AI collaboration. It explores the creative applications and limitations of key AI algorithms such as GAN (Generative Adversarial Networks), VAE (Variational Autoencoders), and Diffusion Models, highlighting their artistic, philosophical, and social implications. The research employs a technical analysis of AI image generation algorithms and programs, case studies of human-AI collaboration, and a discussion of ethical and societal concerns. The findings demonstrate that GAN, VAE, and Diffusion Models can process large datasets to generate innovative and original content, extending traditional artistic boundaries. These algorithms enhance diversity and creativity in artistic expression while unlocking new possibilities for visual exploration. However, challenges such as copyright issues, data bias, lack of transparency, and unclear criteria for assessing artistic value remain significant hurdles. The study emphasizes the importance of Explainable AI (XAI) in addressing these challenges. XAI ensures transparency in AI-generated content, mitigates biases, and clarifies roles in human-AI collaboration. This elevates AI from a supportive tool to a partner that enhances creative and artistic innovation. In conclusion, the research underscores the need for robust legal and ethical frameworks and further development of XAI technologies. AI-based creation holds the potential to redefine artistic creation, offering a transformative paradigm. By fostering ongoing research and discussions, this study contributes to new directions for human-AI collaboration, expanding the frontiers of artistic exploration.