As researchers and private companies teach machines to recognize differentiation in vocal inflection, facial expressions and other cues, experts say the field is ripe for applications in higher education.
While AI already helps colleges automate core functions to improve efficiency, advances in emotion research could expand the role of AI considerably. Adaptive learning and online courses are two potential beneficiaries.
For example, Sutherland says, AI could learn a student’s patterns and adapt course material to improve outcomes, or sense if the student was becoming distracted or bored and switch to a more engaging mode of communication.
Aleix Martinez, a cognitive scientist and professor of electrical and computer engineering at The Ohio State University who has studied affective computing extensively, says researchers seek to make AI more “humanlike.”
“You want to make sure that technology can communicate the way humans communicate,” he says. “The technology has improved, but we are still lacking that human touch.”
MORE FROM EDTECH: See how universities are using AI to boost graduation rates.
Learn from the Movies
Kevin S. LaBar, associate director of the Center for Cognitive Neuroscience at Duke University, was part of a team that developed a neural network capable of classifying images into 11 emotion categories.
Researchers trained the system using photos and screen grabs from movie trailers.
The key, he says, is to train deeply, exposing the system to thousands of images over several years. “Now, these new tools are really permitting insights we didn't have the framework to explore,” he says. “It’s a really exciting time to be looking at emotion more broadly.”