TY - JOUR
T1 - The politics of visual indeterminacy in abstract AI art
AU - Zeilinger, Martin
N1 - Funding Information:
I’m grateful to Ashley Scarlett (Alberta University of the Arts, Calgary), for inviting me to present elements of this work at “Contingent Systems: Art and/as Algorithmic Critique” (Illingworth Kerr Gallery, 2021), and to Tom White, for his generosity in discussing his artistic practice with me. I also acknowledge the financial support in making this article Open Access received from Abertay University’s R-LINCS2 scheme.
Publisher Copyright:
© 2023 ISAST.
PY - 2023/2/1
Y1 - 2023/2/1
N2 - 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.
AB - 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.
U2 - 10.1162/leon_a_02291
DO - 10.1162/leon_a_02291
M3 - Article
SN - 0024-094X
VL - 56
SP - 76
EP - 80
JO - Leonardo
JF - Leonardo
IS - 1
ER -