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July 20, 2019 12:03 am

Emotion-Detection Applications Are Built On Outdated Science, Report Warns

maiden_taiwan writes: Can computers determine your emotional state from your face? A panel of senior scientists with backgrounds in neuroscience, psychology, computer science, electrical engineering, biology, anthropology, psychiatry, pediatrics, and public affairs spent two years reviewing over 1,000 research papers on the topic. Two years later, they have published the most comprehensive analysis to date and concluded: "It is not possible to confidently infer happiness from a smile, angerfrom a scowl, or sadness from a frown, as much of current technologytries to do when applying what are mistakenly believed to be thescientific facts.... [How] people communicate anger, disgust, fear, happiness, sadness,and surprise varies substantially across cultures, situations, andeven across people within a single situation." Neuroscientist Lisa Feldman Barrett, author of the book How Emotions are Made and behind a popular TED talk on emotion, who was an author on the paper, further elaborates: "People scowl when angry, on average, approximately 25 percent of the time, but they move their faces in other meaningful ways when angry. They might cry, or smile, or widen their eyes and gasp. And they also scowl when not angry, such as when they are concentrating or when they have a stomach ache. Similarly, most smiles don't imply that a person is happy, and most of the time people who are happy do something other than smile." The American Civil Liberties Union has also commented on the impact of the study. "This paper is significant because an entire industry of automated purported emotion-reading technologies is quickly emerging," writes the ACLU. "As we wrote in our recent paper on 'Robot Surveillance,' the market for emotion recognition software is forecast to reach at least $3.8 billion by 2025. Emotion recognition (aka 'affect recognition' or 'affective computing') is already being incorporated into products for purposes such as marketing, robotics, driver safety, and (as we recently wrote about) audio 'aggression detectors.'"

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