‘Neuropolitics consultants’ say they know what’s on your mind, even if you’ve left it unspoken.

Maria Pocovi, founder of the Emotion Research Lab (ERL), is using algorithms to identify voters’ unspoken feelings. This ability could start a revolution in political campaigns as targeted messages could push specific buttons in a particular voter cohort.

Bruce Peterson explains how in his article on Pocovi’s invention in the MIT Technology Review:

“We have developed algorithms to read the microexpressions in the face and translate in real time the emotions people are feeling,” Pocovi says. “Many times, people tell you, ‘I’m worried about the economy.’ But what are really the things that move you? In my experience, it’s not the biggest things. It’s the small things that are close to you.” Something as small as a candidate’s inappropriately furrowed brow, she says, can color our perception without our realizing it.

Pocovi says her facial analysis software can detect and measure “six universal emotions, 101 secondary emotions, and eight moods,” all of which interest campaigns anxious to learn how people are responding to a message or a candidate. She also offers a crowd-analytics service to track the emotional reactions of individual faces in a human sea, meaning that campaigns can take the temperature of a room as their candidate is speaking.

ERL’s software is built around the facial action coding system (FACS) developed by Paul Ekman, a famed American psychologist. Pocovi’s algorithm deconstructs each facial image from the webcam into more than 50 “action units,” movements of specific muscle groups. Distinct clusters of action units correspond to particular emotions: cheek and outer-lip muscles contracting at the same time reveal happiness, while lowered brows and raised upper eyelids betray anger. Pocovi trains her system to recognize each one by showing it many reference images from a large database of faces expressing that emotion.