Recently, I wrote a piece about an art forger whose copies of Gaugin, Monet, and other modernists were good enough to fool experts in several countries. But could they fool a neural-net trained on the artists’ work?

That’s what computer scientist Eric Postma is trying to find out. He’s created an artificial-intelligence program called Authentic — which can stare at hundreds of a painter’s works, figure out regularities in his or her style, and then use that knowledge to deduce whether any particular painting is authentic. This also produces an interesting side effect: The program is able to spot patterns in an artist’s technique that no human has noticed before. As the New York Times reports:

By analyzing several hundred low-resolution images of van Gogh paintings downloaded from the Web, the Authentic team still managed to pick out, in hours, patterns that would have taken much longer to detect using manual research — for example, the fact that van Gogh’s use of complementary colors was greater when outlining human figures than it was for other objects in his paintings.

“As data, these Web images are terrible,” said Mr. Berezhnoy. “Nevertheless, our method confirmed an increase in van Gogh’s use of opponent colors. I could tell you that van Gogh started to use blue-yellow opponency in such and such year, and red-green later on, or that he used opponent color to highlight portrait silhouettes and human figures. Do you think I had time to draw those conclusions by studying all 854 paintings?”

That picture above is, by the way, Van Gogh’s “Olive Grove”.