“<i>DeepAesthetics</i> offers a fascinating movement across a triadic relation between critical engagements with artworks, close analyses of machine learning, and the interrogation of both via speculative pragmatism. It will doubtless be of interest to media artists and scholars working in science and technology studies, art practice, cultural and media theory, aesthetic theory, and the philosophy and ethics of artificial intelligence.”

- Matthew Fuller, author of, How To Be a Geek: Essays on the Culture of Software

“In this intriguing thought experiment, Anna Munster moves beyond the familiar approach of studying human experiences with computers to consider whether computation itself, especially in its machine learning guise, can undergo experiences that matter—and that mean something outside the human cognitive system. With this gesture, she puts forward a bold and innovative proposal for seeking radical novelty in a world stuck in familiar patterns, rhythms, and styles.”

- Joanna Zylinska, author of, AI Art: Machine Visions and Warped Dreams

Computation has now been reconfigured by machine learning: those technical processes and operations that yoke together statistics and computer science to create artificial intelligence (AI) by furnishing vast datasets to learn tasks and predict outcomes. In DeepAesthetics, Anna Munster examines the range of more-than-human experiences this transformation has engendered and considers how those experiences can be qualitative as well as quantitative. Drawing on process philosophy, Munster approaches computational experience through its relations and operations. She combines deep learning—the subfield of machine learning that uses neural network architectures—and aesthetics to offer a way to understand the insensible and frequently imperceptible forms of nonlinear and continuously modulating statistical function. Attending to the domains and operations of image production, statistical racialization, AI conversational agents, and critical AI art, Munster analyzes how machine learning is operationally entangled with racialized, neurotypical, and cognitivist modes of producing knowledge and experience. She approaches machine learning as events through which a different sensibility registers, one in which AI is populated by oddness, disjunctions, and surprises, and where artful engagement with machine learning fosters indeterminate futures.
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Anna Munster explores aesthetics, artificial intelligence, and machine learning to understand the contours of computational experience and the possibility to artfully use AI to create new futures.
Introduction: Deep Machines and Surfaces of Experience
1. Heteropoietic Computation: Category Mistakes and Fails as Generators of Novel Sensibilities
2. The Color of Statistics: Race as Statistical (In)visuality
3. Could AI Become Neurodivergent?
4. Machines Unlearning: Toward an Allagmatic Arts of AI
Postscript. On Models of Control and (Their) Modulation
Acknowledgments
Notes
References
Index
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Produktdetaljer

ISBN
9781478031543
Publisert
2025-04-22
Utgiver
Vendor
Duke University Press
Vekt
445 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, UP, 06, 05
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter

Biographical note

Anna Munster is Professor in the School of Art and Design at the University of New South Wales and author of An Aesthesia of Networks: Conjunctive Experience in Art and Technology and Materializing New Media: Embodiment in Information Aesthetics.