One of the key emerging ideas behind machine learning is the notion of generative adversarial networks, or GANs, where at least two neuronal networks are set in a competition, forming a framework of rules in which learning can take place. The more neuronal networks are involved, and the more references are presented to discriminate and learn from, the better and more complex the outcome.

However, one problem that arises in this scenario is the question of context. If a context is solely constructed around art, understood as technique and visual representation, then the result tends to be discussed and analyzed in terms of such a context. If the context of a painting, for instance, is only its visual reference, image quality, and the strokes of the paintbrush, then key aspects of what defines art as a search for questions of being may be ignored or even misunderstood. The visual output of an artwork cannot be neglected, yet it does not represent art alone.

Within the framework of the Art Machines 2 Symposium, the Art Gallery thus acts as a spatial condition, a field in which artworks are not seen on their own or showcased in a vacuum devoid of meaning and critical perspective. Instead, we bring together 27 artworks to form a context in which art is evolving and through which we can articulate further frames of understanding. This context, therefore, allows us to establish a new and more advanced discourse, one based less on stylistic mannerisms or medium, and more on how essential cultural questions and societal concerns can be re-evaluated and re-articulated through the lenses of emerging technologies and computational tools.

Though small in size, our “training set” in this exercise includes works of bio art, digital fabrication, sound art, style GANs, works concerned with the definition of landscape, nature and our global environment, explorations of new urban conditions, political realities in media art or the lack thereof, emotional and emancipatory relationships and, ultimately, what it means to be human within such contexts.

Featured artists:

Refik Anadol & Maurice Benayoun, Nirav Beni, Ben Bogart, Derek Curry & Jennifer Gradecki, Angela Ferraiolo, Varvara Guljajeva & Mar Sola, Daniel Howe & Bill Posters, Sue Huang, Ryo Ikeshiro, Ivan Iovine, Elena Knox, Kwan Q. Li, Javier Lloret, Lukasz Mirocha, Peter Nelson, Provides Ng et al., Maro Pebo, Juan Manuel Piña, Afroditi Psarra, Audrey Desjardins & Bonnie Whiting, Tivon Rice, Mariana Rivera & Sara Zaidan, Vincent Ruijters & RAY LC, prOphecy Sun, Freya Zinovieff, Gabriela Aceves-Sepulveda & Steve DiPaola, Antti Tenetz, Georg Tremmel, Ziwei Wu & Lingdong Huang, and Lan Zhang.

Exhibition curated by Tobias Klein and Rodrigo Guzman-Serrano as part of the Art Machines 2 Symposium, City University of Hong Kong. Sponsored by Croucher Foundation and the U.S. Consulate General in Hong Kong and Macau.

Exhibition website live & archived

Constructing Contexts—Art Machines 2 (intro wall). School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung

Maurice Benayoun and Refik Anadol, DïaloG (2021). Constructing Contexts—Art Machines 2. School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung

Elena Knox, Actroid Series II (2020-21). Constructing Contexts—Art Machines 2. School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung

left: Maro Pebo with Malitzin Cortes & Yun W. Lam, Microbial Emancipation (2020); right: Mariana Rivera & Sara Zaidan, Reflective Geometries (2019). Constructing Contexts—Art Machines 2. School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung

foreground: Kwan Queenie Li, Bull, Ghost, Snake, God [牛鬼蛇神] (2021); background: Juan Manuel Piña & Andrés A. Cedillo, The Mexican AI Artisan (2020-21). Constructing Contexts—Art Machines 2. School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung

Ziwei Wu and Lingdong Huang, Mimicry (2020). Constructing Contexts—Art Machines 2. School of Creative Media, City University of Hong Kong, Hong Kong

photo: Tai Ngai-lung