Appreciate the performative quality of computer-generated art

Should we consider computer-generated digital artworks the same way we evaluate performative events? Can electronic generative art be interpreted as a performance with machines rather than bodies? What if artists, critics and audiences were too focused on results rather than process?

Computer-generated art has been around for over 60 years, ever since early computer users experienced the creative potential of machines originally designed to calculate numbers and calculate calculations too difficult or time-consuming to solve by humans. These computer art pioneers, engineers, and mathematicians such as A. Michael Noll (b. 1939), Frieder Nake (b. 1938), and Georg Nees (1926-2016), wrote instructions that were formally essentially the same as the math problems they usually posed. machinery.

In the way these artists work, a machine is programmed to create as many possible responses to the artist’s instructions as the arbitrary parameters imposed by the latter allow. The two key aspects of early digital generative art were the instructions given to the machine and the calculation of possible outcomes.

odo (the character of an anonymous generative artist), “hfold 1.1” (2021) (image courtesy of the artist)

This orientation is reflected in the works of another pioneer of computer art, Vera Molnár (b. 1924). An exception among the many computer scientists who explored the creative potential of digital technology at the time, Molnár had a background in aesthetics and art history when she produced her first computer-generated artworks in the early 1900s. 1960s. Instead of creating visual patterns heavily inspired by the works of the most popular Op artists of the time as other engineers did – notably Noll’s interest in the works of Bridget Riley – Molnár developed an original style that seems unprecedented, as if it could not have been developed with traditional art tools. Works like “Untitled (5)” (1972) and “In the beginning was the square” (1973) show simple geometric figures arranged by computer according to Molnár’s instructions. These rules allowed the machine to calculate many different results which were then selected by the artist.

The principles of contemporary digital generative art are the same ones that presided over the production of these first works 50 years ago. The works of contemporary artists as different as Rafaël Rozendaal (b. 1980) and Zach Lieberman (b. 1977) do not seem to be the result of a particular interest in the way the work manifests itself visually, but in the potential given by the code they wrote and the arbitrary results calculated by the machine.

The imposition of instructions in order to make things move relatively freely is an artistic practice particularly explored in the last 100 years, since the industrial production of goods and images has led artists to study processes more than results. An example that predates both computer-generated and performance art is the “Telephone Pictures” (1923) by László Moholy-Nagy (1895-1946). In 1922, the artist contacted an enamel factory by telephone and ordered paintings on enamelled porcelain. As the artist tells in his book Summary of an artist, he had the factory color chart in front of him and sketched his canvases on squared paper. “At the other end of the phone, the factory foreman had the same kind of paper, divided into squares. He noted the dictated forms in the correct position. The result of this operation are three painted enamels of different sizes which, beyond their aesthetic value, represent a fundamental moment in the short history of the remote production of works of art.

Among the artists and movements that explored the creative potential of giving instructions and telling their unfathomable results, Allan Kaprow (1927-2006) and the happenings played a fundamental role. Happenings were usually introduced by issuing instructions to the public to make the event truly participatory. The instructions played a fundamental role in many actions carried out by Fluxus artists. An exemplary exhibition was “Art by Telephone”, (November-December 1969), the title of which recalls the above-mentioned Moholy-Nagy experiment carried out almost 50 years earlier. Held at the Museum of Contemporary Art in Chicago in late 1969, the exhibit featured thirty-six artists invited to instruct museum staff on the contributions they were to implement on behalf of the artists. Many of them provided instructions for creating objects and installations, while others tried to make the process itself the actual work, such as Wolf Vostell (1932–1998) who shared a list of numbers phone that visitors dialed to receive instructions for one-minute events. .

A key aspect of performative works of art is that they are implicitly constructed and presented in such a way as to be appreciated for their potential, for the surprise factor they generate in the rules they impose on reality. What makes performance art such a stimulating practice is not only what happens in an observable manner during this or that staging, but the very embodied act of participating, be it in as a spectator, to the action.

On the contrary, digital generative art seems to be appreciated by experts and collectors only for the results it produces, most often ignoring the craftsmanship that went into planning the scenario or the process of calculating the machine. From this point of view, works like “Piece “P-777_D” (2002-2004) by Manfred Mohr (born in 1938) or “Untitled Computer Drawing” (1982) by Harold Cohen (1928-2016) must be appreciated as selected. documenting the potential of their original scripts the same way we look at footage and video recordings of performance art events.

Morteza Shahbake, “OKVE” (2021) (image courtesy of the artist)

Artists using computers to create algorithmic art show only a few of the many possible outcomes, arbitrarily extracted from the flow of the action. If the artist does not stop the machine and let it calculate without extrapolating partial results, what would the real work constitute? Maybe that would be the original script?

The way artists use algorithms to develop art is reminiscent of how pachinko games work. The balls fall vertically through a series of pins and obstacles until they hit a winning target or reach the bottom of the playing field. Part of the thrill of playing this traditional Japanese game is witness the trajectory of the ball behind a transparent plate, hoping that it reaches the cups at the bottom. Looking at the computer generated art is like looking at a stationary pachinko ball that has already reached the cup, setting aside the initial gesture of inserting the ball and looking at the path it took leading to its final position .

From a market perspective, it is much easier to trade stand-alone objects, whether images, sounds, or computer-generated interactive applications; it would be very difficult to do the same with something as volatile and irreplaceable as a machine’s computation or one of Kaprow’s events. As Kaprow himself wrote in the 1961 essay “Happenings in the New York Scene”, their business embodied “the myth of failure, for they cannot be sold and taken home; they In the same way, computer-generated art calls for a deeper and insightful understanding of what it means to create art in collaboration with a machine, a perspective that cares more about performative quality. of its manufacture than of its crystallization in tangible forms.

Christopher S. Washington