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AI Art, Machine Learning and the Stakes for Art Criticism

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The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual's capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.
Nora N. Khan is a writer, editor and curator with a particular interest in artificial intelligence and machine learning. Her previous books include Seeing, Naming, Knowing (Brooklyn Rail, 2019), on the politics and future of machine vision.
Foreword; Introduction; 1 At the Intersection of Techno-utopianism and Techno-pessimism; 2 Ghosts of Sol LeWitt: Mystic Programming; 3 I See a Thing That Looks Like; 4 Mining the Uncanny; 5 Nudging, Scale, and Speed: Recognizing Technocratic Production; 6 The AI Art Exhibition; 7 Critical Translation: From Reveals to Measured Resistance; Notes; Further Reading; Index
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