What is the potential of machine art, and can it truly be described as creative or imaginative?
In July 2013, an up-and-coming artist had an exhibition at the Galerie Oberkampf in Paris. It lasted for a week, was attended by the public, received press coverage, and featured works produced over a number of years, including some created on the spot in the gallery.
Altogether, it was a fairly typical art-world event. The only unusual feature was that the artist in question was a computer program known as “The Painting Fool.”
The unresolved questions about machine art are, first, what its potential is and, second, whether—irrespective of the quality of the work produced—it can truly be described as “creative” or “imaginative.” These are problems, profound and fascinating, that take us deep into the mysteries of human art-making.
Thus far, the Painting Fool—described as “an aspiring painter” on its website—has made progress on all three fronts. By “appreciative,” Colton means responsive to emotions. An early work consisted of a mosaic of images in a medium resembling watercolor. The program scanned an article in the Guardian on the war in Afghanistan, extracted keywords such as “NATO,” “troops,” and “British,” and found images connected with them. Then it put these together to make a composite image reflecting the “content and mood” of the newspaper article.
Leonardo da Vinci recommended gazing at stains on a wall or similar random marks as a stimulus to creative fantasy. There, an artist trying to “invent some scene” would find the swirling warriors of a battle or a landscape with “mountains, rivers, rocks, trees, great plains, valleys and hills.” This capacity might have been one of the triggers for prehistoric cave art. Quite often a painting or rock engraving seems to use a natural feature—a pebble in the wall that looks like an eye, for example. Perhaps the Cro-Magnon artist first discerned a lion or a bison in random marks, then made that resemblance clearer with paint or incised line.
One aspect of artist Harold Cohen’s earlier work was crucial to his taking an interest in artificial intelligence. He felt that “making art didn’t have to require ongoing, minute-by-minute decision making ... that it should be possible to devise a set of rules and then, almost without thinking, make the painting by following the rule.”
Eventually, he found a way to teach AARON to use colors with a simple algorithm. We have limited ability to imagine differing chromatic arrangements, but our feedback system is terrific. A human artist can look at a picture as it evolves and decide exactly, say, what shade of yellow to add to a picture of sunflowers. AARON does not have a visual system at all, but Cohen devised a formula by which it can balance such factors as hue and saturation in any given image.
For more images of Harold Cohen's work: www.aaronshome.com
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