TroublingGAN: generated visual ambiguity as a speculative alternative to photojournalism

Lenka Hamosova

Exposition

TroublingGAN: generated visual ambiguity as a speculative alternative to photojournalism (2023)

Lenka Hamosova, Pavol Rusnák

open exposition

About this exposition

This exposition documents artistic research that engages with generative neural networks and artificial intelligence-driven visual synthesis, the goal being to challenge the limits of the research and question the value of the generated visual outcomes. We present here our experiment with a customised StyleGAN model. In contrast to its utilisation by computer scientists, it has been trained on a heterogeneous dataset, voluntarily exposing the generative neural network to failure while focusing on the unexpected moments of surprise that arise from such a process. Led by the critical thoughts of The Nooscope Manifested (Pasquinelli and Joler 2020), this experiment questions what kind of knowledge generative neural networks produce, whether they could change one’s perspective on studied objects (the dataset) and whether they could function as a viable tool for artistic research. The observed object in this project is the concept of ‘troubling times’ (inspired by ‘Designing in Troubling Times’, the theme of the 2021 Uroboros Festival) — rapid socio-ecological changes caused by shifts in global economic, political and technological power and the subsequent series of troubling events, including the COVID-19 pandemic, violent conflicts and environmental catastrophes. StyleGAN is used as a pattern-recognition and knowledge-production tool to create an intuitive understanding of what this ambiguous term ‘troubling times’ actually means today. During the experimentation process, multiple unforeseen moments and twists happened, offering valuable insights into the nature of synthetic media, generating ethical questions concerning the use of generative neural networks and spawning new propositions for further research.

type	research exposition
keywords	neural network, styleGAN, synthetic media, photojournalism, troubling times, generative neural networks, GANs, visual ambiguity
date	21/12/2023
published	21/12/2023
last modified	21/12/2023
status	published
affiliation	Film and TV School of Academy of Performing Art in Prague
copyright	Lenka Hámošová, Pavol Rusnák
license	CC BY-NC-ND
language	English
url	https://www.researchcatalogue.net/view/1486468/1586300
doi	https://doi.org/10.22501/jar.1486468
published in	Journal for Artistic Research
portal issue	31. 31
external link	https://troublinggan.hamosova.com

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TroublingGAN: generated visual ambiguity as a speculative alternative to photojournalism (2023)

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