MATTHEW BIEDERMAN (QC - CA)
Generative Adversarial Network
(millimeter wave), 2017
ISEA X ELEKTRA
The 28th International Symposium
on Electronic Art edition
16 - 21 May 2023, Forum des images, Paris
Matthew Biederman works across media and milieus, architectures and systems, communities and continents since 1990. He creates works where light, space and sound reflect on the intricacies of perception. Since 2008 he is a co-founder of Arctic Perspective Initiative, with Marko Peljhan working on throughout the circumpolar region.
Biederman was the recipient of the Bay Area Artist Award in Video by New Langton Arts, First Place in the Visual Arts category of Slovenia’s Break21.
He has served as artist-in-residence at a variety of institutions and institutes, including the Center for Experimental Television on numerous occasions, CMU’s CREATE lab, the Wave Farm and many more. His work has been featured at: Lyon Bienniale, Istanbul Design Bienniale, The Tokyo Museum of Photography, ELEKTRA, MUTEK, Ars Electronica, Bienniale of Digital Art (CA), Artissima (IT), SCAPE Bienniale (NZ) and the Moscow Biennale (RU), among others.
Biederman is currently represented by Art45 + Sedition.com and lives and works in Montreal, Quebec.
A Generative Adversarial Network
This work takes its name from the software framework used to create its imagery as a self-referential point in order to reveal not only how the images are created, but also how the idea of the public has shifted in a so-called free society. The parameters of what constitutes an adversary are constantly shifting depending on the context and perspective, but within machinic perception, they remain fixed within the biases of its programmers and the dataset, or society and their polity. For ‘A Generative Adversarial Network’ a machine-learning algorithm was trained with a dataset gleaned from millimeter-wave security scans. Rather than using it for security screening as intended, the algorithm creates new images of imaginary people. This methodology of AI creates new images from random noise by continually updating and re-evaluating the imagery, at times breaking down, becoming confused and starting over - not unlike our global security apparatus.