Editorials & Other Articles

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(26,487 posts) Sat Jan 17, 2015, 12:45 PM Jan 2015

Computers are learning to read emotion, and the business world can’t wait. By Raffi Khatchadourian

http://www.newyorker.com/magazine/2015/01/19/know-feel

. . .

n October, Kaliouby took the Acela to New York to speak at a conference, called Strata + Hadoop World, at the Javits Center. More than five thousand specialists in Big Data had come from around the country—believers in the faith that transformative patterns exist in the zeros and ones that sustain modern life. The talks ranged from “Industrial Internet” to “How Goldman Sachs Is Using Knowledge to Create an Information Edge.” Some of the attendees wore badges for well-known corporations (Microsoft, Dell, G.E.); others were for companies I hadn’t heard of (Polynumeral, Metanautix). While waiting to enter the main hall, I stood beside one of the few women there. Her badge simply said “U.S. Government.”

In the darkened hall, audience members opened laptops, and their screens glowed. In the greenroom, Kaliouby reviewed her notes and did breathing exercises. Onstage, she declared that it was the first time a scientist in her field had been invited to join “the Big Data conversation”: a throwaway line, but one with a remarkable implication—that even emotions could be quantified, aggregated, leveraged.

She said that her company had analyzed more than two million videos, of respondents in eighty countries. “This is data we have never had before,” she said. When Affectiva began, she had trained the software on just a few hundred expressions. But once she started working with Millward Brown hundreds of thousands of people on six continents began turning on Web cams to watch ads for testing, and all their emotional responses—natural reactions, in relatively uncontrolled settings—flowed back to Kaliouby’s team.

Affdex can now read the nuances of smiles better than most people can. As the company’s database of emotional reactions grows, the software is getting better at reading other expressions. Before the conference, Kaliouby had told me about a project to upgrade the detection of furrowed eyebrows. “A brow furrow is a very important indicator of confusion or concentration, and it can be a negative facial expression,” she said. “A lot of our customers want to know if their ad is offending people, or not really connecting. So we kicked off this experiment, using a whole bunch of parameters: should the computer consider the entire face, the eye region, just the brows? Should it look at two eyebrows together, or one and then the other?” By the time Kaliouby arrived in New York, Affdex had run the tests on eighty thousand brow furrows. Onstage, she presented the results: “Our accuracy jumped to over ninety per cent.”

. . . more