AI, AS SEEN AT THE END OF OWNERSHIP
2025-03-22 → 2025-06-22
The exhibition brings together 19 artists and groups from around the world, utilizing a diverse range of media including plotter drawing, generative art, AI system, video, game, animation, and robotic interactive installation. It explores how technology reshapes art traditions and fosters new conceptual expressions through human-machine collaboration. This exhibition is a response to the history of conceptual art and a question for the future: as algorithms infiltrate into art practices, what evolutionary paths will conceptual art follow?
Generative art and conceptual art share roots in the 1960s yet have long followed different paths. Generative art uses computer algorithms to produce visual forms that are both consistent and endlessly varied; conceptual art, by contrast, emphasizes putting ideas ahead of physical objects, challenging traditional art’s focus on materiality and narrative. Today, the widespread use of artificial intelligence has blurred this boundary. Text-based prompts have replaced complex programming as the core directive for creation. Latent Diffusion Models simplify image generation through dimensionality reduction, allowing artists to control visual output by simply entering text. This machine-like “conceptualized” output not only echoes the idea of conceptual art pioneer Sol LeWitt’ s idea that “The idea becomes a machine that makes the art,” but also raises practical questions regarding issues such as algorithmic “hallucinations” (unexpected results due to data bias), hidden computational layers, and deepening biases in large-scale model training.
The exhibition is divided into three sections. The first section presents generative art alongside contemporary works that engage with technology. On one hand, generative art offers an intuitive understanding of computation, recursion, and systematic design; on the other, it invites us to reconsider that these “algorists” are not merely generating similar yet varied lines through repetitive rules, but are conducting cross-disciplinary cultural experiments that probe the essence of technology.The second section uses cutting-edge technology to explore the purpose of art in an AI context, challenging the limitations, noise, and unexpected outcomes produced by computation as well as the social biases that may be reinforced through recursive processes. The final section revisits the issue of “authorship.” Although this topic has been widely discussed in the context of internet and post- internet art, the era of artificial intelligence offers a completely new framework for understanding creation and ownership. Shaped by the evolution from Web 1.0 through 2.0 to 3.0, art ownership is beginning—or may have already shifted—toward a shared model with machines. Algorithms can analyze, process, and recognize images, thereby “possessing” a form of knowledge or understanding. This notion of “algorithmic ownership” is a metaphor that, in a data-driven age, challenges not only the boundaries of copyright law but also brings new insights into the nature of digital objects.