My original vision for this article was to cover the development of computer art from the 50’s to the 90’s, but it turns out there’s an abundance of things without even getting half way through that era. So in this article we’ll look at how Lovelace’s ideas for creativity with a computer first came to life in the 50’s and 60’s, and I’ll cover later decades in future articles.

I stray from computer art into electronic, kinetic and mechanical art because the lines are blurred, it contributes to the historical context, and also because there is some cool stuff to look at.

Early days

The first electronic art

Around 100 years after Babbage and Lovelace discussed the Analytical Engine, a mathematician named Ben Laposky was inspired by an article written in Popular Science which suggested that decorative patterns could be created using oscilloscopes. [3]

Laposky began creating his “electrical compositions” in 1950, using a cathode ray oscilloscope along with electronic circuits like sine wave generators. He captured the moving outputs using long exposure photography. In later pieces, he rotated filters in front of the screen to add colour to the images.

Early Interaction

A lot of digital art has an input and an output. For example, the input could be a pseudorandom number and the output could be a geometric drawing, or the input could be music and the output an animation. In some work the output is fed back into the system, creating a feedback loop. This is the “circular causality” of cybernetics.

The process of creating generative art is often cybernetic, as we iterate and develop work based on the outputs we see from our algorithms. An artwork itself can also be cybernetic, as in Gordon Pask’s MusiColor (1953).

MusiColor was a mechanical and electronic system designed to be used by musicians. Sounds from their instruments were input via microphone and analysed for frequency, attack and rhythm. This input determined the output from various lights and pattern or colour wheels controlled by servo motors, with mappings that developed over time. If the input became repetitive, the system would adjust its output to generate more variety in the visual patterns.

As performers would adjust their playing in response to the visual output, Pask wrote, “the machine is designed to entrain the performer and to couple [them] into the system’’. Performers also felt they could train the machine to produce the sorts of patterns they preferred. [7]

It’s pretty nuts how advanced this piece was, in terms of technology and thinking around interaction. However it was perhaps before its time and, despite being exhibited in several different locations, it was plagued by technical issues and often struggled to suit its surroundings. It was “difficult or impossible to make genuine use of the system’’ and MusiColor was shelved in 1957. [7]

Cutting Edge Technology

Computer artists of the sixties often worked laboriously, feeding instructions into machines on punch cards and then waiting hours or days for the results to be drawn by mechanical plotters, or using complex techniques involving things like magnetic tape, cathode ray tubes and microfilm. The speed of iteration is one of the things I love about contemporary digital creation and I can hardly imagine how waiting so long for each output would change the creative process.

The Pseudorandom sixties

Artists like Vera Molnar, Manfred Mohr, Georg Nees, Frieder Nake and A Michael Noll heralded the advent of generative computer art. These artists – who were mostly actually scientists or engineers – used code to create algorithms and began to think about the place of the computer in the art world, as well as exploring randomness and chaos.

Vera Molnar: algorithms and Exploration

Vera Molnar was unusual in this group as she had worked towards art her whole life and did not have a background in science. She gained access to a computer by going to the Paris University computing centre and explaining to the head of the department that she wanted to use a one to make art. After giving her a look which implied to Molnar that “he was considering whether he should call for a nurse to sedate me”, he yes anyway. [15]

Manfred Mohr: Evolving traditional art

Manfred Mohr was a saxophonist and painter and then in 1970 he had the opportunity to work with a Control Data 6400 computer and Benson plotter at the Météorologie Nationale.

It’s clear to see how his artistic and musical career shaped his algorithmic work. His early computer art was “influenced by atonal music, modern Jazz and abstract expressionism.” [18]. Abstraction, geometry and semiotics are common themes in his work both before and after the introduction of computers.

Mohr initially sought to capture his painting style in an algorithm, as above, but later said:

One “should assume that old techniques of drawing and imagination are not to be imposed on the machine (although this would be possible), but should develop a priori a vocabulary which integrates the computer into the aesthetic system, that means: to use this powerful instrument not only as an interpreter.” [19]

I believe he’s saying that, while we can use the computer to simulate traditional artistic methods, it is more interesting to use the computer in entirely new ways, developing its own aesthetic language instead of using it to simulate physical media.

Mohr’s later work focused on rule based systems and geometry, taking advantage of the power of the algorithm.

This idea is still discussed today, as much generative and digital art does seek to replicate or play off analogue methods – often very successfully, while some work is more focused on exploring the possibilities of the machine itself.

Frieder Nake: Art Advances

In 1971, computer artist Frieder Nake wrote a piece titled, perhaps surprisingly, “There should be no computer art”, in which he considers the debate about bringing computers into art from more angles. [20]

He argues that computer art has not contributed “to the advancement of art, if we judge ‘advancement’ by comparing computer products to all existing works for art.” [20] However, on the other hand, he had no doubt that computer art has found “interesting new methods” and that there will be “an entirely new relationship between the creator and the creation.” Nake focuses on the place for computers in the process, rather than the outcome.

Georg Nees: Drawing on Maths and Science

In these early days, the duality of artist and scientist was inevitable due to the limited access to computers outside of scientific settings, but it’s something that has persisted to the present day. The algorithms, geometry, precision and techniques of computer art are appealing to artists who are interested in maths and science. At the same time, the randomness and rule systems of generative art have a rich conceptual interest, drawing the mathematical enthusiast into conceptual and artistic thought.

Georg Nees first studied mathematics and physics and worked as a mathematician for Siemens, before studying philosophy under Max Bense and publishing his thesis, ‘Generative Computergraphik’ in 1969.

A Michael noll: Computerising Traditional Art

Another Bell Labs alum, A. Michael Noll, worked alongside Georg Nees and Frieder Nake and together they were known as the “3N” computer pioneers. Noll first started experimenting with creative outputs from computers after seeing an interesting plotter error produced by a colleague. In a 1962 paper about his work, Noll said he wanted to avoid “unintentional debate (…) on whether the computer-produced designs are truly art or not” and instead referred to the “machine’s endeavours” as “Patterns”. [22]

Despite this hesitancy to classify his work as art, he created several pieces that directly referenced well known traditional artworks.

Alternative Processes

Some artists found ways to use computers in their practice outside of plotting algorithms on paper. Here we’ll look at some video art, mechanical art, dance and more.

Lillian Schwartz

In 1968 Lillian Schwartz created her kinetic sculpture Proxima Centauri, which was exhibited at MoMA in their exhibition “The Machine as Seen at the End of the Mechanical Age” [23].

The sculpture consisted of a translucent white dome sitting atop a base which contained coloured lights, a projector, a tank of water which tilted to create ripples, a motor from a Singer sewing machine and rotating painted slides. These mechanisms projected images onto the white dome when visitors stepped onto a pressure sensitive pad. Proxima Centauri was brought back to life in recent years and can be view in detail in a film by The Henry Ford. [24- film].

Bela Julesz: Psychology and Art

On another axis of the famed intersection of art and science, is psychology. Psychologist and computer scientist, Béla Julesz worked at Bell Labs from the late 50s, where his research into human visual perception was accelerated by the use of computers to generate images and animations.

He is probably most known for his work with stereoscopic vision, particularly his invention of the “random-dot stereogram”, which later led to the autostereogram (more commonly known as a Magic Eye picture). In a random-dot stereogram, two similar images are laid side by side, with one area displaced. By crossing their eyes, the viewer can see a 3D form appear, even when the image is random dots – demonstrating that depth perception in humans is mechanical and not dependent on contextual clues. [25]