Chris Dorland “New Day”

Lyles & King

poster for Chris Dorland “New Day”
[Image: Chris Dorland "Untitled (instinct mode)" (2020) Acrylic polymer, pigment, ink, gesso, UV coating on linen, 68 x 46 in.]

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Lyles & King presents New Day, a solo exhibition of new work by Chris Dorland. New Day consists of a suite of large scale paintings on linen and two hyperreal data-driven video works. This will be the artist’s second exhibition with the gallery. The exhibition title references the inherent contradictions in technology’s relentless optimism and fetishism for progress. While appearing optimistic, New Day also leaves open the possibility for what is unknown.

For over a decade Dorland has been working at the intersection of two contradictory practices: painting and new media. The artist has been developing and refining a unique compression of both analog and digital languages into a singular and dense aesthetic rife with both unexpected beauty and extreme chaos. The artist uses a variety of screens, scanners, drones, gaming consoles, and other optical devices to compose distorted, glitching works that conjure up the increasingly tenuous boundaries between physical and digital environments. Neither fully abstract nor functionally representational, Dorland’s work allows us to apprehend the force of intrusive technologies as they increasingly distort our understanding of reality. The resulting vision is a haunting meditation on contemporary life ensnared within a web of digital labyrinths of our own creation.

The paintings on view are Dorland’s most complex effort to date to collapse paint and digital technologies into a single indistinguishable skin. Oscillating between decayed abstraction and 4k ultra resolution–Dorland’s new paintings infer the god’s eye view of topographic visualizations and video game POV’s while simultaneously rendering commonplace, yet intimate, minutiae of daily life such as folder clutter from the artists desktop with hypergraphic detail. Seemingly lit from within–the paintings emit a cold white glow that is contrasted against an abyss of rich blacks and intense synthetic color. The paintings’ dense surfaces optically confuse and question our ability to distinguish between the handmade artifact and what comes from beyond the digital threshold: leaving the viewer with no apparent ability to adequately discern between the two.

In addition to the painted works, Dorland has developed ambitious data-driven video works. Both animations use generative adversarial networks (GAN) as their starting point. GAN is a class of machine learning. Generative modeling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities or patterns in input data in such a way that the model can be used to generate or output new examples that plausibly could have been drawn from the original dataset. During the first few months of the 2020 quarantine, the artist created a series of animations using GAN algorithms. Those GAN experiments were subsequently used as the basis to animate the skins of two lifelike entities that are each the focus of their own unique video works within the exhibition: Untitled (species) and Untitled (speciesII). Each video brings to life a digital creature encased within a digital womb.

Chris Dorland (b. Montreal) is a Canadian/American artist living and working in New York. His work has been exhibited in FRONT INTERNATIONAL: The Cleveland Triennial for Contemporary Art, Cleveland, US; Nicoletti Contemporary, London, UK; Super Dakota, Brussels, BE. He has exhibited in galleries such as Marc Selwyn Fine Art, Los Angeles, US; Sikkema Jenkins, New York, US; Rhona Hoffman Gallery, Chicago, US. His work is in the permanent collections of the Whitney Museum of American Art, New York, US; Bronx Museum of Art, New York, US; and Neuberger Museum of Art, New York, US among others. He is Director-at-Large at Magenta Plains.

Media

Schedule

from February 12, 2021 to March 14, 2021

Opening Reception on 2021-02-12 from 14:00 to 18:00

Artist(s)

Chris Dorland

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