What is Generative Art and Where is this Creative Technology Leading Us?

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What is Generative Art?

Few forms of art truly capture our technological evolution so completely as generative art. Broadly speaking, generative art can refer to aesthetic works made through any autonomous, non-human system, guided or overseen by an artist to produce random, non-predictable results. 

Most generative art today is computer-generated, incorporating randomly produced variable elements to make up the composition. Generating randomness is at the heart of generative art. The unpredictability created through autonomous systems is the point and also the gratifying aspect of generative artworks.

Autonomous systems can be defined as functions that can be carried out independently in a defined but changing environment. However, randomness without order is only chaos. Therefore, the role of the artist is to put rules in place around the creation of the work, limiting certain variables and defining the parameters of change and chance to generate a unique aesthetic experience. 

In addition to creating works of visual art, generative techniques have been implemented in the fields of music, poetry, and architecture to stimulate new arrangements of audio tones, language syntaxes, and physical forms. Inspiration for autonomous systems can be derived from geometrical phenomena and naturally occurring patterns in biology, chemistry, mechanics & robotics.

While it is true that most generative art does indeed involve math and code it isn’t as complicated as most people make it out to be. Yes, creating art might already be tricky in itself but you don’t need a computer science degree to create generative art. Although non-programmers may feel intimidated by the math behind this evolving art form, in this article you’ll be enlightened as to what generative art is, the origins of generative art, and how you can get started producing your own generative art works.

History of Generative Art

The impulse behind Generative Art in the visual arts can be traced back to the end of the 19th century and the boom of the Industrial Revolution when cubists began to experiment with visual deconstruction in painting. More specifically, in Proto-Cubism we see a radical geometrization of form and a reduction or limitation of the color palette bringing about the practice of imposing creative limits around the graphic representation.

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Pablo Picasso, 1909, Brick Factory at Tortosa (Briqueterie à Tortosa, L’Usine, Factory at Horta de Ebro), oil on canvas. 50.7 x 60.2 cm, (Source entry State Museum of New Western Art, Moscow) The State Hermitage Museum, Saint Petersburg.

These techniques transformed the way we view classical subject matter by breaking down scenes into geometrical forms with multiple vantage points. The mathematically inspired visual unveiling essentially changed the way we see art and illustrated an unseen world of visual code that underlies our reality.

Along similar lines, art movements that followed, such as Futurism and Constructivism, pushed the relationship between art, math, and technology further. As modernist art movements continued to evolve, with styles such as Dadaism and Surrealism, conventional definitions of art and creativity continued to be challenged, introducing more randomness into the art-making process. 

With the advent of Pop Art, we see artists like Andy Warhol establish a kind blueprint for replication and production of his screen printing techniques by which his artworks could be created by assistants other than himself, challenging the role of the artist and ownership in the art-making process. 

But the first usage of the term ‘Generative Art’ came about in 1960 in relation to the first newly generated computer graphics. Here, imaginative mathematicians, like Georg Nees, set out to create what was then referred to as ‘Computer Art’, where Nees used tools like the flatbed drawing machine below to create purely aesthetic drawings, which he describes as ‘useless’ rather than technical.

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Flatbed drawing machine ZUSE Z64, photograph by Tomasz Sienicki.

Nees continued to innovate in his incorporation of randomization in his breakthrough work, Schotter or ‘Gravel’ in German.

In Gravel, first made in 1966, Nees programmed an increasing variable positioning of each cube, as the cubes descend in order. The more randomness programed into the given set, the more the forms descended from order into chaos.

To see a comparison of the variation in the end image that results from using this same code check out this page for a side-by-side view and tutorial from contemporary digital artist Jim Plaxco.

Not all randomisation in Generative Art however need be computer-based. In 1968, Sol LeWitt shook up the artworld with his first Wall Drawing, or as he describes it, ‘non-objective art.’ The Wall Drawings of Lewitt consisted only of a set of instructions for the drawing which was to be carried out by the Museum or Gallery.

The instructions laid out a set of rules or parameters for the execution of the art world. In this case, the introduction of randomised elements, came in both the ambiguity for missing instruction and the unique set of individuals who physically carried out the instructions in a particular environment.

In the example above, from Wall Drawing #118, fifty points were to be drawn, evenly distrubuted, on a wall surface at random and connected with lines. The texture of the wall, the spacing of the dots, the color of the lines, the medium of the drawing utensil, and even the size of the work are undefined and left to the museum to decide, making each drawing unique.

Over the course of years, hundreds of Wall Drawings were conceived and carried out.

How to make Generative Art?

If you happen to be savy with math, code, algorythms, or javascript you may not have much trouble creating automons environments and imposing certain definitions and rules to guide the process. But, if you are like me, you may prefer a software program that can handle the back-end for you.

There are two approaches to creating Generative Art. There is a freestyle approach where you are essentially using programs or data limitations to discover pleasing harmonies. On the other hand, you may already have a completed idea or form in mind are are looking to tweak it or discover something new in this existing structure.

A fun tool to get a taste of a simple Generative Art software program you can play with online is from Acrylicode. Here you can start with a simple scribble and fiddle about with a few parameters such as scale, angle, zoom, and repetition to create shapes and forms that seem light years away in relation to the original drawing. Check this video out below to watch me virtually fiddle about.

Another cool online tool was created by Michael Bromley. Here, instead of beginning with a simplified sketch, you can upload any picture or image, adjust the parameters of certain digitizing interpretations of that image, and create an entirely new piece.

For the more adventurous there are, of course, tutorials that can teach you some simple code to create your own specifications for this kind of digital image generation, likewise there are more sophisticated software programs to help bring your concepts to life. A nice website for some tools, tutorials and inspiration is from Generative Hut.

Conclusion

When I first started researching the subject I was a little sceptical. I immediatedly assumed that computers could taint human creativity by sucking the soul from it in some dry distopian way, however, technology is only a vehical and not the driver (not yet at least). The real act of creation comes in the borders we set around that limitless ball of creative potential.

Generative Art by definition seems limitless and today’s technology allows artists with or without programing skills to harness that chaos to produce original and unique works of beauty and harmony. When you add 3D software, algorythims, and even AI advanced computer processing and data analysis, the sky is the limit.

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