HUMAN-MACHINE CREATIVITY
Collaboration and Autonomy in Ai Art
DOI:
https://doi.org/10.33871/sensorium.2026.13.12107Keywords:
AI art; human–AI collaboration; generative adversarial networks; creativity; art creation.Abstract
This article explores the role of artificial intelligence (AI) in art creation by analysing the work of two notable artists, Sougwen Chung and Mario Klingemann. By adopting a case study approach, we analyse Chung’s Recursions series and Klingemann’s Memories of Passersby I as two different models of human–AI interaction in art: collaborative co-creation and machine autonomy. The findings show that Chung’s work is based on a continuous interaction between human gestures, biofeedback systems, and robotic responses. This process demonstrates a fluid collaboration between human and machine. Meanwhile, Klingemann’s work emphasizes algorithmic autonomy through generative adversarial networks (GANs). The artist guides the system’s outputs through curatorial and aesthetic decisions. Comparing these two models contributes to the literature on collaboration, creativity, and agency in AI art.
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