Thursday, March 12, 2015

Omnipotence Paradox 2015: Art Forgery Variant

The omnipotence paradox is the one that smart-ass fifth graders ask before they learn about category mistakes:
"Can [insert omnipotent being] create a stone so heavy that [O.B.] cannot lift it?
From The Atlantic:

Robot vs. Robot
Can a computer forge a painting well enough that it fools the algorithms designed to detect fakes?

 
Beautiful mathematical patterns are hidden in the chaos of Jackson Pollock’s famous drip paintings. The repeating designs—fractals of grey, black, and yellow—were first uncovered in 1999 by Richard Taylor, a physicist from the University of Oregon. He proposed his findings in the journal Nature, and later suggested that computers could analyze the geometric patterns within the brush strokes to detect a Jackson Pollock fraud from an original.

To demonstrate his methods, Taylor and his colleagues planned to use the unique signatures they found to make a Jackson Pollock fake good enough to dupe art experts. “However, we concluded that to generate this work would represent the dawn of a new and unwanted era,” Taylor told me in an email. “So we shelved the plan.”

As robots increasingly work (and play) in ways that once seemed fundamentally human, Taylor believes the art world is headed toward a turbulent time filled with difficult questions: If a computer can fake a painting, can it also fool the computers designed to detect the fakes? How can the programs designed to spot fakes stay a step ahead of the programs designed to generate them? The idea, he said, could trigger a particularly ominous cycle, considering the millions of dollars that could be made from forgeries.

The art world, Taylor said, has just passed through the first phase of answering these questions. His team, and more recently a team led by the computer scientist Lior Shamir from Lawrence Technological University in Michigan, has found that computers can use fractal analysis to distinguish between real Pollocks and imitations. Shamir and his colleagues analyzed more than 100 paintings, including 26 original Jackson Pollocks, for traces of fractal patterns. To do so, the paintings were digitized in 640,000 pixels then cut into 16 different segments. Then, the computer would analyze the paintings segment by segment and determine whether each portion’s fractal patterns matched the mathematical features in Pollock’s work. The computer, it turned out, was right about 93 percent of the time. Shamir and his team published their findings in the International Journal of Art and Technology.

Shamir believes that computers will eventually be able to create artwork indistinguishable from a person-made painting, an idea that’s still controversial in the art world. But robots are already dabbling in artistic pursuits—everything from acting to dancing to painting....MORE