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Can Technology Decipher Human Emotions Better than Humans?

Posted By Prucia Buscell, Friday, July 8, 2011

People who have autism have trouble interpreting facial expressions. It turns out the rest of us aren’t very good at it either, but science can enhance our sensibilities. Emotional reader technology isn’t sci-fi any more—it’s a burgeoning filed.

Rosalind Picard, an electrical engineer and computer scientist at the Massachusetts Institute of Technology Media Lab and doctoral candidate Rana el Kaliouby designed eye glasses that let wearers know the emotions of a person they are looking at. The glasses hold a camera the size of a grain of rice, with a wire attached to a tiny computer. Sally Adee describes her experience with emotional X-ray glasses in an engaging New Scientist story. Initially, she thought Picard was intently interested in her incisive questions. Wearing the glasses, she was chagrinned to learn Picard’s facial expressions actually reflected feelings of confusion and disagreement. Worse, Picard was bored. Adee heard this report through a headphone attached to the glasses, and a red light told her to stop talking. If Picard had been smiling and nodding, Adee would have gotten a green light.

As a researcher at the University of Cambridge in the UK, el Kaliouby wanted to find ways to help autistic people communicate better. She worked with Simon Baron-Cohen, a psychologist who directs the Autism Research Center at Cambridge, to identify emotional facial states that would be more helpful than an earlier designation of basic expressions that focused on being happy, sad, angry, fearful, surprised, disgusted or contemptuous. . They settle on six that reflect common yet nuanced emotional states—thinking, agreeing, concentrating, interested, confused and disagreeing.

When Picard and el Kaliouby worked on their design, they found the average person interprets only 54 percent of those states correctly. Their software correctly identifies 64 percent of the expressions. Watch Picard’s TED talk—there are more than 10,000 facial expression variations that can change every second, so it’s no wonder we miss a lot of them. She also notes that devices that measure engagement show audiences perk up with live performers and shut down with PowerPoint. Picard and el Kaliouby established a company called Affectiva, which sells expression recognition software to companies that want to measure how people really feel about their advertisements and products. The two have worked with colleagues to fine tune their software to pick up subtle but meaningful differences in expressions that look similar. As Judy Garland sang, "Smiles” make us happy and blue. If you have a web cam, you can test your own smile here.

Others at the MIT Media Lab developed a small electronic sociometric badge that people can wear around the neck to measure several aspects of their social interactions, such as voice volume, pitch and tone, physical proximity to others, and language patterns: whether they were talkative or taciturn and whether they tended toward monologue or dialogue. Initially, they called it the "jerk-o-meter”. Members of groups who wore the devices experimentally became more socially sophisticated after seeing their own interactions analyzed. Alex Pentland, Daniel Olguin and others at the MIT Lab founded a start-up called Sociometric Solutions. A Forbes magazine story tells how Bank of America made an interesting change resulting from badge-generated data. Instead of staggering the break times of call center employees, they aligned times to allow more people opportunity to chat. Information sharing expanded networks, improved teamwork and collaboration, and ultimately improved productivity. The technology has also been used in healthcare and other fields.

Is there a dark side? Picard emphasizes emotional reader technology must be used ethically and voluntarily. Simon-Cohen warns greater emotional sophistication doesn’t always come with empathy.

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