Artificial Intelligence in the Evolving Nature of Visual Art

Ryan Seo
Seoul Foreign School

 

Abstract

The idea of AI-assisted artwork was established through the program AARON by Harold Cohen. By breaking down multiple images’ components, it creates an accurate representation of authentic items within our society. This program’s development dispersed a creation method classified as Generative Adversarial Networks (GANs). The prominence of this network allowed for a more nuanced arsenal of artistic creativity among artists. Using GANs, many artists and organizations implemented AI-controlled softwares such as AICAN (artificial intelligence creative adversarial network) and Perception Engines by Tom White.
The origins of data visualization trace back to a unique combination of science and design, much like the idea of AI-assisted artwork. Through AI programs, independent and collaborative groups of artists have made many projects, such as the interactive and automated data visualization in the Art Nabi Center. These practices build on the more traditional interactive art methods established in the late twentieth century by artists like Rirkrit Tiravanija and others. The addition of AI into this practice has drastically changed the process of visual creation, especially in regards to interactive artworks.
Organizations such as Artists Who Code and programs like Dynamic Brushes have aided in the transition of artists into programming. On the other hand, some programmers utilize their skills to create a portfolio to get recruited into renowned companies such as the designer Jong Min Kim.
Through various computer programs which evolve over time to become more complex and detailed, AI art is proving itself a significant shift in artmaking processes. Through independent and collective organizations, the publicization of this form of artmaking has been on a constant increase within the 21st century.

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