SURVIVAL: 500 works by Kevin Abosch (2021)

500 works informed by data pertaining to humankind's struggle to survive. Using a battery of machine-learning algorithms, encryption algorithms, the blockchain and paint, Abosch works ritualistically to distill emotional value in these charged works. Click to learn more about SURVIVAL


Sun Signals is comprised of 1010 NFT works by conceptual crypto-artist Kevin Abosch, informed by analysing sun cycles and solar radiation on Earth and training on this data with deep-learning algorithms. The work is both a celebration of the star that powers all life processes on Earth while reminding us of the lethal spectre of climate change precipitated by industry. Sun Signals are generated "off the grid" using the artist's solar-powered computer servers. The images and metadata are stored on Arweave's Permaweb. The project is part of the artist’s larger vision “1111” which includes a DAO (decentralised autonomous organisation) and a “green” satellite project “1111 KOSMOS” from which art will be “space-dropped” to collectors on Earth. Abosch views the entirety of this project as an intervention leveraging the very technology it endeavours to evolve. The entire collection can be viewed on OpenSea

89b23 / 80bd5 / c6dc8 (2020)

Cryptographic keys, some truncated, sublimate into a lingual arcana and a repository of sacred knowledge.

Weaponized Data (2020) & Concurrent Genocides (2020)

In this series of works, Abosch starts with a "commented-out" (//) subject for which he collects copious amounts of pertinent and otherwise relevant data. The horizontal yellow lines are synecdochic segments of a line the artist has been generating on a computer server since January 3, 2018. Abosch uses the yellow line to serve as a proxy for immeasurable value within a continuum. He then begins a back and forth ritual in which a series of algorithms train on the input data while the artist reacts to the output during multiple stages of "refinement." The positions of the three arrows on each line are determined by the final output of the algorithmic processing. The top line is the "control" and the bottom line is the "amplification" creating a visual rhythm and highly distilled form of the subject. Abosch refers to this process as "Hybridized AI."

From Nascent Space (2019-2020)

The scientific method moves from a hypothesis to an experiment and ultimately yields a result. It’s understandable that scientists and technologists are result-driven. It is the result that yields the empirical data that speaks to an experiment’s success and failure. Indeed, the very reputation of the scientist and the technologist is a function of presenting results to their peers. My own interest in the scientific method has waned over the years. Empirical data can be of great practical use, but as an artist I’m more interested in process, ritual and insights gleaned long before the result.

With respect to deep-learning algorithms, I force complications by limiting and corrupting the input data. What would ordinarily comprise the latent space is sublimated into what I call “nascent space.” Nascent space exists within a gaussian, or normal distribution of data but holds the prima materia from which discovery and creation are born. It is in this nascent space that I find truths not necessarily apparent within results. — Kevin Abosch

// classify.discriminate @ CADAF Miami 2019

Kevin Abosch installs work at CADAF (Contemporary and Digital Art Fair) @ Mana Contemporary in Miami, Florida / December 5-8, 2019

// classify.discriminate (2019) - installation with vinyl post-mortem bag

Classification and discrimination are methods used in the development of artificially intelligent systems. With Black men and boys in America 2.5 times more likely to die during an encounter with police than white men and boys, the fact that society’s implicit biases already exist in computer code cannot be ignored.

Kevin Abosch @ National Museum of China

5th Arts and Science International Exhibition and Symposium (TASIES 2019) / Nov 1 - Dec 1 2019

Hypothetical Reconstruction: Seeds (2019) - acrylic, photographs and generative photographs on canvas 3 panels - 72in x 108in

In Hypothetical Reconstruction: Seeds, Kevin Abosch uses photography and a generative adversarial network (GAN) to create a corpus of natural and synthetic seeds (Swiss chard) that individually and collectively serve as a proxy for the purpose of distill ing emotional value. In a ritualistic back-and-forth process, Abosch uses machine learning (ML) and his own intuition to generate, discriminate against, classify and prune visual data. This feedback loop persists until the artist is convinced that a lost or forgotten truth has been “reconstructed.”

line work @ Christies NYC

ART+TECH Summit / June 25th 2019 / Christies New York: Kevin Abosch generates a digital line which grows at a rate (pixels per minute) determined by the processing of input data (images, audio, etc) through a chain of algorithms. The artist treats this ritual as necessary to reconfirm his understanding that the emotional value of the input data is immeasurable and can therefore be represented by any segment of the line or the line in its entirety. The segment is synechdochic and serves as final proxy in these works.

One day you won't be able to pull that rabbit out (2019) - 40 x 60 in / archival pigment print on dibond

Participants I (2019) - 40 x 60 in / archival pigment print on dibond

The incident with the bus on Madison Avenue (2019) - 40 x 60 in / archival pigment print on dibond

The morning after the Met Gala (2019) - 96 x 4 in / acrylic cylinder filled with acrylic paint