Portrait of Daniel-Henry Kahnweiler, Pablo Picasso, Art Institute of Chicago, Wikipedia, Date Accessed: May 6, 2020.
“But they are useless. They can only give you answers.” – Pablo Picasso
· If Picasso were alive today, he would no doubt be taken aback by the exponential advances in computing that have been made in the past few decades. A far cry from the giant mechanical brains and mere calculating machines of the 1960’s, today’s computers look like yesterday’s science fiction. Glancing at Picasso’s 1910 masterpiece “Portrait of Daniel-Henry Kahnweiler”, you have to wonder what modern day computers would make of such abstract works of art. Deep learning visual processing systems have become experts at tagging our friends in photos, but could they derive meaning from such a composite image of loose shapes and forms? Plenty of AI software packages can create art. Recognizing what unique pieces make an abstracted version of Daniel-Henry Kahnweiler is a little more tricky. To accomplish this feat a deep learning system would need to perform feature extraction on the image and somehow make a connection to not only Picasso’s particular style, but mimic his emotive state at the time. This seems like a tall order for the current state of machine learning. Nonetheless, advances in machine learning are happening all the time in areas as diverse as art and psychology. For instance, the field of artificial empathy is blooming with robots and virtual agents that can both detect and respond to a wide range of human emotions. Is it too far fetched to see this technology harnessed to mimic specific emotive states, including those associated with artistic expression? Could these abilities then be used to more fully “understand” Picasso’s mental state while he was painting this iconic portrait in 1910? If all of this was somehow quantifiable, the benefits to society at large would be immense. Psychology would have a new window into the creative mind and art could be appreciated from new and exciting perspectives. Once the layers of abstraction are peeled away, understanding the creative mind may become more logic driven. Perhaps then we could better understand the black box containing this logic.