Anna Munster: DeepAesthetics as computational experience: engaging machine learning through process philosophy and art
All are welcome to Aesthetic seminar
Info about event
Kasernen, Building 1584, Room 124
Many routinely performed operations of data preparation and optimisation in machine learning(ML)-driven AI seem to be solely quantitative. Yet their execution simultaneously organises data relations according to vectors of similarity and difference. At the very moment data is quantitively operated upon by the statistical methods of ML, it is also re-spatialised and re-configured with ‘hidden’ or latent potential for pattern and relation. Slippages, then, between quantity and quality compose the ‘experience’ of ML at large.
In this talk, I propose that ‘deepaesthetics’ might be used to probe the quantitative-qualitative oscillations characterising contemporary computational culture. ‘Deepaesthetics’ is a disjunctive contraction gluing together two worlds with seemingly little concern for each other: deep learning, a subfield of machine learning using neural network architectures; and a branch of philosophy traditionally concerned with how judgements about formal or sensory qualities come to be made. Yet in the proliferation of style transfer and the synthetic creation of genres and moods in music, deep learning’s mainstream cultures already affirm and update formalist and cognitivist aesthetic traditions. Alternatively, deep learning’s (qualitative) operativity lends itself to being thought via concepts from process philosophy, especially Gilbert Simondon’s ‘alagmatics’, with its knowing of technical systems via their dynamic operations. Taken together with techniques honed through critical AI art, I suggest that ‘deepaesthetics’ might be torqued to name a different aesthesia of indeterminacy for autonomous systems, at odds with a ‘predictive’ society.
Anna Munster is a Professor of Art and Design at the University of New South Wales, Australia and co-director of its newly formed Autonomous Media Lab. Her research currently focuses on new interventions into AI. She has written: An Aesthesia of Networks (2013, MIT) and Materialising New Media (2006, Dartmouth University); articles on media assemblages, networks and platforms, media art and process philosophy in Theory, Culture and Event, Journal of Cultural Analytics, Inflexions; contributed to Affects, Interfaces Events (Imbricate, 2021) and has co-authored with Adrian MacKenzie for the anthology Distributed Perception (Routledge, 2021). Anna is writing a new book Deepaesthetics: on computational experience in a time of machine learning. She is a practicing artist working across sound, video, data, and autonomous systems.