Worldmaking in Art and AI
Scholar Peli Grietzer’s research asks what machine learning can tell us about the structures of ambient aesthetics–moods, vibes, and other qualities that give us the sense of an artwork’s (or art world’s) formal unity. In a noted 2017 essay A Theory of Vibe, Grietzer had addressed these artistic structures through the framework of autoencoders—neural networks trained to develop visual representation algorithms for digital media. He argued that the aesthetic organization of artworks is functionally parallel to how AI technologies construct a coherent body of information.
For this engagement at EMPAC, Grietzer considers what is unique about the structures of meaning within art and poetic thought, through articulating the worldmaking properties of AI’s mathematical systems. The talk draws on his recent research connecting poetic form, art and aesthetic philosophies of the Romantic movement, and the architectures of artificial intelligence. For Grietzer, machine learning’s computational structures illustrate art’s power to effect meaning through a unique material force.