It’s the expression of horror seen all around the world: A gaunt man with hollowed eyes stands on a path by the water, holding his head in his hands. His mouth is open in an oval scream as his body appears to be receding into a topsy-turvy world set against a blood-red sky.
Our reasons for being enthralled by Edvard Munch’s “The Scream” have always seemed as mysterious as the painting itself. Not so, according to Ahmed Elgammal, a Rutgers University professor who has developed an algorithm for evaluating a painting’s creativity.
“The results show that humans are no longer the only judges of creativity,” Elgammal writes in The Conversation.“Computers can perform the same task.”
Using a series of mathematical transformations, Elgammal and his colleagues at the school’s Art and Artificial Intelligence Laboratory have devised a system for determining through computerized visual analysis the creative worth of any given painting. But first, they had to define creativity.
Ray Kroc, one of the early entrepreneurs behind the success of McDonald’s, called it “a highfalutin’ word for the work I have to do between now and Tuesday.” It comes more easily to some than others: Lil Wayne once told MTV, “I ain’t never out of the zone, so I don’t know what the zone look like or smell like. I’m always creative.” And T.S. Eliot famously deemed creativity impossible without anxiety as its handmaiden.
The algorithm defers to Kant. In his theory of aesthetics, the philosopher called being original and “exemplary” the two principal conditions for artistic genius. So Elgammal’s parameters of creativity are similarly two-fold: originality and lasting influence.
Here’s how he explained it:
Using computer vision, we built a network of paintings from the 15th to 20th centuries. Using this web (or network) of paintings, we were able to make inferences about the originality and influence of each individual work.
Through a series of mathematical transformations, we showed that the problem quantifying creativity could be reduced to a variant of network centrality problems – a class of algorithms that are widely used in the analysis of social interaction, epidemic analysis and web searches. For example, when you search the web using Google, Google uses an algorithm of this type to navigate the vast network of pages to identify the individual pages that are most relevant to your search.
Any algorithm’s output depends on its input and parameter settings. In our case, the input was what the algorithm saw in the paintings: color, texture, use of perspective and subject matter. Our parameter setting was the definition of creativity: originality and lasting influence.
The scientist ran an analysis of 1,700 paintings throughout history. Among those which received high creativity scores were “The Scream,” Kazimir Malevich’s first Suprematism paintings and paintings by Piet Mondrian and Georgia O’Keeffe. The painting that ranks first in the batch is Picasso’s “Ladies of Avignon,” while da Vinci’s “Mona Lisa” is notably absent from the top picks. The algorithm didn’t like that one much at all.
Elgammal notes in The Conversation, “We don’t want our research to be perceived as a potential replacement for art historians, nor do we hold the opinion that computers are a better determinant of a work’s value than a set of human eyes.”
“Rather, we’re motivated by Artificial Intelligence (AI),” he notes. “The ultimate goal of research in AI is to make machines that have perceptual, cognitive and intellectual abilities similar to those of humans.”
In other words, this formula is probably a closer approximation of how creativity will be judged during The Singularity than it was when Munch put brush to canvas. And it’s unlikely that anyone will be using it in art classes any time soon. As Picasso himself once said, “The chief enemy of creativity is ‘good’ sense.”