Episode 25 Myths About Emotion Science | The Feelings Lab
Published on Aug 30, 2022
Join Dr. Alan Cowen, founder of Hume AI, Dr. Dacher Keltner, founding director of the Greater Good Science Center and Professor of Psychology at the University of California, Berkeley, and host Matt Forte as they discuss Myths About Emotion Science. Does the face ‘reveal our emotions’? What does science really say about how people express their feelings? We discuss the real complexity and nuance of facial and vocal expressions, and revisit what Darwin meant when he said that expressions are “purposeless.”
To kick us off, Hume AI CEO Dr. Alan Cowen discusses the meaning of expressions, and explains why the question of whether they "reveal our emotions" is a bit of a misdirection.
Dr. Dacher Keltner discusses how debates surrounding emotion science are often independent from the data, and how non-peer-reviewed articles and public statements have popularized the notion that expressions have no meaningful correlation with emotion.
Later in the episode, Hume AI CEO Dr. Alan Cowen discusses the misconception that AI is being built to "measure our emotions," and how it derails attempts to build transparency, control, and empathy into technology that is already teaching itself about human expressive behaviors.
Dr. Dacher Keltner shares the importance of Darwin's "The Expression of the Emotions in Man and Animals" and how it anticipated more recent discoveries revealing how our expressions coordinate social interaction.
Next, Hume AI CEO Dr. Alan Cowen discusses the three sources of evidence that humans evolved to form expressive behaviors, including studies of different species, developmental stages, and cultures.
Dr. Dacher Keltner and Hume AI CEO Dr. Alan Cowen discuss why popular debates seem to center on the face to the exclusion of other modalities of emotional expression, such as the voice.
Subscribe
Sign up now to get notified of any updates or new articles.
Share article
Recent articles
Are emotional expressions universal?
Do people around the world express themselves in the same way? Does a smile mean the same thing worldwide? And how about a chuckle, a sigh, or a grimace? These questions about the cross-cultural universality of expressions are among the more important and long-standing in behavioral sciences like psychology and anthropology—and central to the study of emotion.
How can artificial intelligence achieve the level of emotional intelligence required to understand what makes us happy? As AI becomes increasingly integrated into our daily lives, the need for AI to understand emotional behaviors and what they signal about our intentions and preferences has never been more critical.
For AI to enhance our emotional well-being and engage with us meaningfully, it needs to understand the way we express ourselves and respond appropriately. This capability lies at the heart of a field of AI research that focuses on machine learning models capable of identifying and categorizing emotion-related behaviors. However, this area of research is frequently misunderstood, often sensationalized under the umbrella term "emotion AI"--AI that can “detect” emotions, an impossible form of mind-reading.