Step right up, ladies and gentlemen, and behold…the eighth wonder of the world. No, not King Kong, I’m afraid. But how about a computer that can read and interpret human emotions and mental states?
That would be from Affectiva, a Boston-area startup co-founded by Roz Picard, a 20-year veteran of the MIT Media Lab. Picard (see photo, right) is the founder and director of the Media Lab’s Affective Computing research group, and she has done extensive work in computer vision, machine learning, and human-computer interfaces, with applications in autism communication, health and wellness, education, marketing, advertising, and other areas.
Picard is speaking at this Thursday’s Xconomy “6×6” event (Six Cities, Six Big Tech Ideas) in Boston. In advance of her appearance there, I sat down with Picard at Affectiva’s offices this week to get a demo of the company’s technology and to talk a little about the future of emotional and gestural interfaces.
One of the demos involved a computer tracking my facial expressions via webcam (and also my heart rate via blood flow to my face) while I watched a series of TV commercials. Based on indicators like raised eyebrows, smiles, or a furrowed brow (see example, below), the software tried to figure out how engaged, interested, amused, or disturbed I was during the course of each ad. It’s hard not to be self-conscious during all this, but I’m pretty sure the computer concluded: this guy hates all commercials. (And since I haven’t smiled since 1995, we’ll enlist my fellow editor Erin Kutz for the live demo on Thursday.)
Affectiva also will be rolling out a new product on Thursday—one that has applications in finance and healthcare, among other industries—but I’ll let Picard speak for that when the time comes.
Meanwhile, I asked Picard whether the field of affective computing would continue to advance incrementally (like speech recognition, say) or whether it would undergo a breakthrough of some kind. “I think it’s going to make some leaps,” she said. “There’s going to be a lot more happening by indirect measurement—nonverbal [cues] that people don’t really think machines can do. That’s going to really progress.”
To me, Picard’s work exemplifies what truly big ideas are about—for the first 20 years or so, they might be more interesting scientifically than commercially. But once the technology and marketplace gets to a certain point, a viable business can be built around them, even as the science continues to advance. And then who knows what will happen?
We’re looking forward to a fantastic 6×6 program and some great networking this Thursday (you can register here). Hope to see you there.
