What Does AI Want from Art?

Visual Cultures Public Programme with Matthew Fuller and Naja Grundtmann

There is a proliferation of claims, from various kinds of actor, about what artificial intelligence can do for art: what it can do in, or as art. In this lecture we aim to ask rather what does AI want from art? In what ways does art provide kinds of evidence to test, material to work on, or problems to break apart that are helpful for aspects of the development of AI? In what way does art exemplify qualities that AI, as it is currently predominantly organised, would like to be able to claim? The lecture opens with an engagement with the cultural significance of creativity and the stakes of approximating creative behaviour in AI. In framing concepts of creativity, its association and attributes, we discuss the prestige and strategic advantages of re-reading and showcasing the operation of AI systems in proximity to creativity as an aspect of intelligence that surpasses the merely procedural, but also how it too has been described procedurally. The second part addresses technical challenges in AI for which art has been instrumental in both the framing of the problem and the formulation of its solution. In this discussion we look at two key ways art is mobilised as material to be reworked by AI to articulate its own problematics: visual ambiguity, and stylistic expression. In the last part of the lecture we propose a reading of what is attractive in using artworks as source data by thinking through how abstractions operate in and as culture.

Matthew Fuller is Professor of Cultural Studies at Goldsmiths. His books include How to Sleep: The Art, Biology and Culture of Unconsciousness (Bloomsbury 2018), How to Be a Geek: Essays on the Culture of Software (Polity 2017), with Olga Goriunova, Bleak Joys: Aesthetics of Ecology and Impossibility (Minnesota 2019) and with Eyal Weizman, Investigative Aesthetics: Conflicts and Commons in the Politics of Truth (Verso 2021). He is a member of the editorial collective of ‘Computational Culture, a journal of software studies’ http://www.computationalculture.net/

Naja Grundtmann is a researcher in the Department of Communication, University of Copenhagen. Her main area of research is located at the intersection of aesthetics, machine learning technology, and visual culture. She obtained her PhD Convolutional Aesthetics: A Cultural and Philosophical Analysis of the Perceptual Logic of Machine Learning Systems from the University of Copenhagen, Department of Arts and Cultural Studies in 2022.

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