The Politics of Visual Indeterminacy in Abstract AI Art

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Abstract

In Perception Engines and Synthetic Abstractions, two generative AI art projects begun in 2018, Tom White experiments with visual abstraction to explore the indeterminacy of perception, interpretation, and agency. White’s AI systems produce images that will be interpreted as abstract artworks by human viewers, but which also confront human audiences with the realization that what is here deliberately rendered indeterminable for them will remain near-perfectly legible for AI-powered image recognition systems. This difference in perceptual and interpretive agency foregrounds an underlying politics of visual indeterminacy. White’s projects thus increase awareness of how machine vision—for example in automated online filtering systems—can diminish the horizon of what human audiences can or cannot see in an AI-driven digital cultural landscape, and how, in the process, underlying biases are normalized and human viewers become habituated to the dramatic shrinking of perceivable/viewable online image content mediated by AI.

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APA

Zeilinger, M. (2023). The Politics of Visual Indeterminacy in Abstract AI Art. Leonardo, 56(1), 76–80. https://doi.org/10.1162/leon_a_02291

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