AI Can See. Can We Teach It To Feel? Posted on : Nov 30 - 2019

We’ve made great strides in the field of computer vision, to the point where self-driving cars equipped with artificial intelligence (AI) can effectively “see” their surroundings. But can we teach AI to “feel” something about what it sees? The folks at Getty Images think we can.

At first blush, the idea that AI could “feel” something would seem to be pretty far-fetched. Feelings in general are closely intertwined with our human identities. How any one person feels about something is bound to be different than how another feels. Feelings are, by definition, subjective. In fact, it’s tough to find a more subjective topic than “feelings.” So how does that mesh with the objective functionality of computers?

The solution is relatively straightforward, according to Andrea Gagliano, a senior data scientist with Getty Images.

Just as a computer vision program attacks the identification problem by breaking an image down into constituent features (or vectors) and comparing them to known entities, Getty is training deep neural network algorithms to be on the lookout for certain elements in the images themselves to ascertain clues about the emotions that humans will attach to them.

The trick, Gagliano says, is encoding those various human emotions into vectors that are associated with the images. For each emotion or feeling that Getty’s data scientists select, such as “authentic” or “in the moment,” the company will assemble a collection of images that in some way represent that feeling or emotion. Each image has anywhere from 100 to 1,000 features or variables that go into building that vector, which can then be used to infer new images. View More