Casey Reas, A Mathematical Theory of Communication

Casey Reas. A Mathematical Theory of Communication, 2014. Inkjet print Two walls: 167 × 198.25 inches; 167.5 × 190.75 inches. Commission, Landmarks, The University of Texas at Austin, 2014. Photo by Paul Bardagjy.

Press play to listen to the audio guide.

Press play to watch the artist video.

audio transcript

I’m Christiane Paul, Adjunct Curator of New Media Arts at the Whitney Museum of American Art and associate professor in the School of Media Studies at The New School in New York, and will give a bit of background for Casey Reas’ project commissioned for Landmarks, the public art program of the University of Texas at Austin. Casey’s artwork is titled A Mathematical Theory of Communication and consists of a mural on two separate walls in the Gates Dell Complex. The project borrows its title from a highly influential article of the same name, which was written by Claude Shannon in 1948 and is considered one of the founding texts in the field of information theory. While the artwork’s title might suggest a technologically or scientifically driven exploration, the project is highly visual and experiential.


Over the past fifteen years Casey Reas has emerged as one of the leading artists in the field of software art. His works have been exhibited in more than one hundred solo and group exhibitions at venues around the world. Casey Reas currently is a professor at the University of California, Los Angeles, and received a master’s degree in Media Arts and Sciences from MIT. Together with fellow MIT student Ben Fry, he initiated and created Processing, an open-source programming language and visual environment for coding.


Casey Reas’ projects—his Process series, in particular—have explicitly explored the art-historical connections between software art and conceptual art such as the works of Sol LeWitt, which place an emphasis on instructions and focus on concepts rather than objects. Casey Reas’ commissioned mural in the Gates Dell Complex is positioned right next to a large LeWitt wall drawing, also part of the Landmarks collection.


Casey’s commissioned project is both a continuation of his previous works and a departure from their focus. A Mathematical Theory of Communication uses images from mass media and broadcast television that were shown as part of the artist’s exhibition ULTRACONCENTRATED at New York’s bitforms gallery in 2013.


Casey Reas’ project visually reinterprets Shannon’s theory of communication and the signal. Shannon famously proposed that messages are transformed into a signal by a transmitter, then sent through a channel—such as a cable or band of radio frequencies—then decoded by a receiver and finally delivered to a destination, be it a human or machine. In Casey’s murals, an original source image is “encoded” into a signal through an algorithm. As viewers of the artist’s data landscape, we become receivers who decode the imagery.


The abstract visuals on Casey Reas’ mural seem familiar and recognizable, and at the same time uncertain, and constantly emerging. They have qualities of painterly abstraction and sometimes seem to suggest a legible original source image. In the end, however, they deny legibility by seemingly putting the viewer in the middle of the computer vision algorithm that was used to transform the original imagery. In a poetic and visual way, the mural raises the question how digital images communicate their message and how we decode and perceive them.

activity guides

Curated Musical Playlist

Casey Reas, A Methematical Theory of Communication, 2014.

American, born 1972


Over the past fifteen years, Casey Reas has emerged as one of the leading artists in the genre of software art, defining both the practice in this field and the theoretical discourse surrounding it. In 2001 Reas partnered with fellow MIT student Ben Fry (born 1975) to initiate and create Processing, an open-source programming language and visual environment for coding. Today artists, designers, and students around the world use Processing for visual prototyping and for programming images, animation, and interactivity.


Reas' software art typically explores systems, specifically their emergence and underlying instructions and conditions. Instructions form the basis of all generative art, in which an autonomous system—such as a machine or computer program—creates a work of art based on rules outlined by the artist. The instruction-based nature of software art points to art-historical roots in conceptual art. Reas explicitly references the work of Sol LeWitt (1928–2007), who generated works through a set of written instructions for others to interpret.


A Mathematical Theory of Communication blends conceptual art and information science by merging aspects of both in order to create an experiential data landscape. For this commission, Reas captured television images with an antenna, then processed the images using algorithms—or “instructions”—he designed. The abstracted images were processed again, generating some forty thousand results, from which Reas chose two perspectives with converging energy. The images were inkjet printed to create the mural on two walls.


The title of this piece is borrowed from a highly influential article (1948) by Claude Shannon (1916–2001) that is considered one of the founding texts of the field of information theory. Shannon proposed that messages are transformed into a signal by a transmitter, then sent through a channel, decoded by a receiver, and finally delivered to a destination. Reas used the title to capture the visual and conceptual theory of communication unfolding in his art, emphasizing that as viewers, we become receivers who decode the imagery. While the title of the work suggests a technologically or scientifically driven exploration, the project itself is highly visual, conceptual, and experiential.

Casey Reas, A Mathematical Theory of Communication, 2014. Photo by Paul Bardagjy.
Casey Reas, A Mathematical Theory of Communication, 2014. Photo by Paul Bardagjy.

Location: North building of The Bill & Melinda Gates Computer Science Complex & Dell Computer Science Hall (GDC)

GPS: 30.286389, -97.736667