Wasteful Computation: The Case for Simpler Algorithms in Computer Art and Music

Algorithmic and generative art has a history which runs parallel with the introduction of computers. The recent fascination with generative AI obscures its links to historical predecessors. Present discussions of whether something made by a computer can be art are in certain ways similar to the discussions that were raised when computer art and music were new, although the large-scale appropriation of prior artworks is a crucial difference. Critical reflection on AI in art is often focused on copyright issues and the changing roles of artists, but too often one of the most important aspects has been left out, namely the enormous energy consumption of the data centres that run current AI models. This, and other environmental consequences, puts large-scale AI on a direct collision course with any sustainability goals. Simpler, more efficient algorithms which do not rely on the appropriation of other artworks remains a promising alternative for digital art. A wide range of negative side-effects have been noticed as a consequence of the widespread adoption of AI, not limited to its use in art. Ranging from a decline in critical thinking and other cognitive and creative skills to hypothetical existential threats to humanity, these broader issues cannot be entirely separated from a debate about generative AI in an art context. A widespread adoption of generative AI also has cultural implications, such as potentially creating an echo chamber effect, as will be discussed primarily with examples from music. The main argument in this essay is that opaque, proprietary AI models are neither good for the environment, for culture in general, or for artists, who have much more to gain from writing simple code themselves.