Abstract
The emergence of deep learning since the mid-2010s and its successful application to creative activity challenges long-held anthropocentric conceptions of art and music. The impact of these technologies in the artistic realm are both exciting and frightening. Yet, while the industrialization of artificial intelligence is happening at a disturbingly fast pace, it is also very specialized, favoring extractive techniques that feed on massive amounts of human-generated data. The restrictive and extractive ethos that propels this industrial revolution represents only a fragment of the actual possibilities of machine learning systems in the hands of artists, musicians, and composers. In this presentation, I discuss alternative approaches to machine learning creation that rest on the embodied performance of agents happening in the real world, in real time. Through my own work and by calling upon contemporary and historical examples of works of media art and music, I discuss the creative potential of such agent-based systems, both in their ability to generate metamorphic behaviors as well as in their impact on artistic practice. Finally, I discuss how these agent-based creative approaches rest on the development of complex relationships between the artist, the agents, and the audiences, one that questions contemporary definitions of art and music beyond the human species.
Bio
Sofian Audry is an artist, scholar, Professor of Interactive Media within the School of Media at the University of Quebec in Montreal (UQAM) and Co-Director of the Hexagram Network for Research-Creation in Art, Culture and Technology. Their work explores the behavior of hybrid agents at the frontier of art, artificial intelligence, and artificial life, through artworks and writings. Audry's book Art in the Age of Machine Learning examines machine learning art and its practice in art and music (MIT Press, 2021). Their artistic practice branches through multiple forms including robotics, installations, bio-art, and electronic literature.
Watch stream
This RITMO Seminar Series is embedded in the EmAI workshop.