In recent years, artificial intelligence has rapidly transformed the landscape of visual culture and artistic production. This article examines the current condition of AI art after the initial wave of technological enthusiasm and public controversy. Rather than focusing on the technical novelty of generative systems, the discussion explores how AI reshapes the concept of artistic authorship, the aesthetics of contemporary image production, and the cultural economy of visual media. Through selected case studies—including the works of Refik Anadol, Mario Klingemann, Trevor Paglen, and Sougwen Chung—the article analyzes different artistic approaches to machine learning, algorithmic creativity, and human–machine collaboration. These examples reveal that AI art is not simply a new visual style but represents a broader shift in how images are produced, distributed, and interpreted within digital culture. By examining both the creative possibilities and the ethical challenges associated with dataset-driven image generation, this essay argues that the future significance of AI art lies less in technological spectacle and more in critical engagement with the infrastructures that shape contemporary visual systems. Ultimately, AI does not signal the disappearance of artistic authorship but introduces a new condition in which authorship becomes distributed across networks of data, algorithms, and human decision-making.
Anna Zhang (Mon,) studied this question.