Art is an expression of a human being’s emotion and interpretation of the world around them, often intended to envoke an emotional response from the observer. So how then can a computer, a machine that thinks only in terms of 1s and 0s, be programmed to create a work of art? Is it even possible?
According to Casey Reas, co-creator of the creative coding software Processing, it is. There’s a whole artistic genre called generative art, defined as being created with the use of an autonomous system, and Processing is at the forefront of this. Artists, designers, architects, programmers and complete novices alike can come to the software to experiment and learn to make visually interesting images, like Diana Lange’s Lisa above.
Talking about the program, Reas describes its ambition to “ruin the careers of talented designers by tempting them away from their usual tools and into the world of programming and computation” and “turn engineers and computer scientists to less gainful employment as artists and designers”.
Reas’ inspiration for Processing came from his own experience and experiments with the artistic process: he outlines a set of rules and allowing the program to go over multiple iterations of a rule to create art. It often starts out with a line, a circle or another basic shape and repeats over and over again, with some random variation added to give a different result every time. The computer generated images below were based on a fairly simple rule set which Reas referred to as Process 6:
* Position 3 large circles on a rectangular surface.
* Set the center of each circle as the origin for a large group of Element 1.
* When an Element moves beyond the circle edge, return to origin.
* Draw a line from the centers of Elements that are touching.
* Make the shortest line black and longest white with varied grey between.
Another such artist is Jon McCormack, who focuses on electronic media and generated artificial life. His Morphogenesis series (2001 – 2004) uses custom computing software to create biological models based on native Australian plant species. A 3D geometric model of the flora is created from the growth algorithm, which can be considered as a kind of ‘digital DNA’, which can then be rendered in a series of digital images.
Though many people claim that the generative method is too easy and cannot be considered real art because there is little to no human input in it’s creation or final aesthetic, McCormack makes it clear that the media has increased his creativity and allowed him to create artificial life and impossible worlds that wouldn’t have surfaced with traditional media:
“The computer has shown me things about the world that I could not have known, understood or seen in any other way. I see and appreciate nature in a fundamentally different way than before … I use a computer for the simple reason that the work I create with it would not be possible in any other medium.”
— Jon McCormack 1994
It is also worth considering that, although the models are generated by the computer, McCormack took inspiration from nature and the environment around him, selecting certain behaviours and attributes and used these to create his codeing. McCormack also decided how the final image looked in terms of perspectives and framing and, in Reas’ Processing images, certain iterations of the code are selected as final prints out of an essentially infinite number. Can it not be considered an influence of an artist’s mind that they have chosen one particular image to represent an entire coded concept?
Another interesting aspect of generating images from software is ownership and creative recognition. If a beautiful, provocative image is created and becomes world renowned, who is credited as the artist? Is it solely the person who arranged the image that is responsible? If someone adds to someone else’s code to create something, is the original programmer a contributing artist? What about the developer of the software itself that has defined the way in which you can create the art – can they lay claim to artwork made from their platform? Could a hacker obtain the code and end up with a ‘genuine original’ of the series?
This idea of handing over control for a piece of art was explored in the work of abstract artist Sol LeWitt. Instead of using a computer, LeWitt designed wall drawings for gallery installations and had other people create them from a set of basic rules.
Originally, when creating his Wall Drawing #16, LeWitt had draftsmen draw up his piece from his instructions due to concerns about practicality and its time-consuming nature. His later drawings came embrace the idea of generative art. Wall drawing #260, which was first installed at the San Francisco Museum of Modern Art in June 1975, is shown below and is a great example of this concept.
The instructions for creating the image is given to artists, trained assistants or even novice volunteers so they can install their own interpretations of the rules. Although each one is of a similar style, they will differ slightly from gallery to gallery. LeWitt considered his method of art to be like a composer and his symphony: the concept and key components are set in stone by the artist and each person implementing it will have their own style and approach to it, like an orchestra taking on a famous piece of music.
Computers can be used as a tool to open up a whole new genre of creativity and self expression, whilst also encouraging the often contrasting worlds of art and computing to come together in a new way. Add to that the increasing presence and capability of artificial intelligence and one day we might see real art being made by machines. For some that might be an depressing snapshot of computers ‘taking over’, but to me it’s an exciting thought. But don’t worry, we’re still a long way off. So while we’re waiting, why not check out some of the best Google Deep Dream images created by running existing images or even random noise through it’s image recognition neural networks over and over. There’s more information over here.
This post was inspired by the Creative Coding course hosted by FutureLearn and Monash University.