Another kind of authenticity: the visual simulacra of artificial intelligence
杉山 将, LI Kang-hua · Digital Creativity · 2025
The rapid proliferation of visual simulacra generated by artificial intelligence (AI) necessitates a critical examination of their authenticity. This study investigates the authenticity of these simulacra by establishing a framework for evaluation, drawing on imitation theory and the theory of simulacra and imitation. It explores the philosophy of AI technology to elucidate the logic by which AI creates visual simulacra, identifies key technological characteristics in AI visual models, and scrutinizes the authenticity of AI-generated simulacra, elucidating their function as metaphors for reality within the context. Our analysis shows that data and computing form the foundational bedrock of AI visual representation, suggesting that AI simulacra offer a unique form of authenticity that complements our understanding of the world. This study provides insights into the complex relationship between AI visual generation and authenticity, aiding our understanding of coexistence with AI and offering guidance for developing AI visual generation technologies.