Normally, people’s reactions to art are considered subjective — Munch’s The Scream might instill a foreboding anxiety in you, but do absolutely nothing for your friend. However, artist Wassily Kandinsky feels that abstract art, what people would perhaps consider the most emotionally subjective form of art, is actually completely objective. He suggests that the emotional objectivity of abstract art lies in the characteristics of the colors and their interactions with one another. This would mean it can be taught to a computer.

Though artificial intelligence may be learning what love is, it has not yet been able to identify why certain things evoke certain emotions — in the case of a painting, for example, why a blue blob would evoke sadness, whereas some red squiggles would evoke anxiety. A team from the University of Trento, led by Nicu Sebe, set out to prove his theory, and took to the Museum of Modern and Contemporary Art of Trento and Roverto.

Using machine vision, they looked at 500 abstract paintings, analyzing the shapes and lines, as well as the color distribution. The team then fed the machine information on how 100 people felt about the paintings, and the machine was able to accurately identify emotions inspired by specific elements of art. The identified emotional ties, such as black colors and pointed shapes evoking a gloomier emotional state, are fairly common knowledge among real-life humans. Dark colors and severe angles inspire a negative feeling, whereas lighter colors and softer angles inspire a positive feeling.

Once the machine was able to correctly match the emotional response to the 100 participants’ opinions, the Trento team tested it with new artwork that wasn’t initially scanned to help calibrate the system. The computer predicted the expected human emotion inspired by each painting, and had an 80% accuracy rate after those results were matched up with the opinions of the 100 participants.

Luckily for those of you fearing an impending robocalypse, the aim of the study is to further the progress of machine-created art, rather than creating an artificial intelligence that knows about our greatest fears. If a machine can identify emotions as related to art, it could conceivably create art with the intensity of a being able to be passionate. Simon Colton of the Imperial College of London notes that art as a whole could benefit from machine-created art, because machines can do certain things humans cannot, such as scanning the entirety of a social network for inspiration. Penn State University’s James Wang suggests applications for machines understanding artistic emotion that aren’t about creating art, such as an image search being able to accurately categorize results by emotion, or computer parental controls that have an emotions filter. We simply hope this study will lead toward robots being able to make us some comfort food when they identify we’re feeling down.

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[Image credit: Laura Warburton]