AI Helping Machines to Get Better at Understanding Emotions


Two thousand seventeen certainly was an emotional year for mankind. While homo sapiens continue to yell at Alexa and Siri, the actuality of people’s willingness to pursue virtual relationships over human ones is startling.

In a recent documentary by Channel 4 of the United Kingdom, it was revealed that Abyss Creations is flooded with pre-orders for its RealDoll AI robotic (intimate) companion. According to Matt McMullen, Chief Executive of Abyss, “With the Harmony AI, they will be able to actually create these personalities instead of having to imagine them. They will be able to talk to their dolls, and the AI will learn about them over time through these interactions, thus creating an alternative form of relationship.”

The concept of machines understanding human emotions, and reacting accordingly, was featured prominently at AI World a couple weeks ago in Boston. Rana el Kaliouby, founder of artificial intelligence company Affectiva thinks a lot about computers acquiring emotional intelligence. Affectiva is building a “multi-modal emotion AI” to enable robots to understand human feelings and behavior.

“There’s research showing that if you’re smiling and waving or shrugging your shoulders, that’s 55% of the value of what you’re saying – and then another 38% is in your tone of voice,” describes el Kaliouby. “Only 7% is in the actual choice of words you’re saying, so if you think about it like that, in the existing sentiment analysis market which looks at keywords and works out which specific words are being used on Twitter, you’re only capturing 7% of how humans communicate emotion, and the rest is basically lost in cyberspace.” Affectiva’s strategy is already paying off as more than one thousand global brands are employing their “Emotion AI” to analyze facial imagery to ascertain people’s affinity towards their products.

Embedding empathy into machines goes beyond advertising campaigns. In healthcare, emotional sensors are informing doctors of the early warning signs of a variety of disorders, including: Parkinson’s, heart disease, suicide and autism. Unlike Affectiva’s, Beyond Verbal is utilizing voice analytics to track biomarkers for chronic illness. The Israeli startup grew out of a decade and half of University research with seventy thousand clinical subjects speaking thirty languages. The company’s patented “Mood Detector” is currently being deployed by the Mayo Clinic to detect early on signs of coronary artery disease.

Read the source article at RoboHub.