One of the more extravagant claims made by tech companies is that they can detect emotions by analyzing photos of our faces with machine learning systems. The premise is sometimes dressed up in claims about “micro-expressions” that are below the threshold of human detection, though some vendors have made billions getting security agencies to let them train officers in “behavior detection” grounded in this premise.
A panel of eminent psych researchers have signed an open letter condemning these products as grounded in “outdated science.” The authors cite more than 1,000 journal articles that show that facial expressions are complex and cannot be classified using the techniques promoted by the self-interested commercial peddlers of emotion detection systems: a scowl is not a reliable indicator of anger, nor is a smile a reliable indicator of happiness.
We have arrived at a long-overdue and extremely welcome techlash, in which Big Tech’s promises about how it stores and manages our data are being looked at with the skepticism they deserve. But many of these critics are remarkably unskeptical about the claims Big Tech makes about the efficacy of its products, taking at face value Big Tech’s sales-literature boasts about being able to detect and manipulate our opinions.
If we’re ready to believe that Big Tech lies about its taxes, its infosec practices, its anti-harassment policies, its privacy policies, its lobbying activities, and everything else it claims about itself, shouldn’t we also ask whether its products actually work?
It may well be that Big Tech is full of people who believe that its products work, just as the private equity world is full of money managers who believe that they can outperform a simple, low-load index fund. Those money managers are wrong. Perhaps Big Tech’s would-be mind-control-ray inventors are similarly self-deluded.
“It is difficult to get a man to understand something, when his salary depends upon his not understanding it!” -Upton Sinclair
The review of studies covering the production of facial expressions during emotional events indicates lack of support for the common view. The research shows, for example, that a smile might signal submission instead of happiness. Moreover, a dearth of systematic and controlled observations of facial movements and emotion in people from remote cultures limits knowing the conditions under which facial expressions may be linked to specific emotions. Barrett and colleagues suggest that using neutral phrases, such as “facial configuration” or “pattern of facial movements” might be more scientifically accurate than the misleading phrases “emotional expression” or “emotional display” given that each pattern of facial movement does not necessarily signal a specific emotion.
Studies of how people perceive emotions from facial expressions also failed to strongly support the common view. When individuals are asked to match facial expressions to emotions they can reliably do so, but when they are asked to generate the emotion label from a facial expression, reliability is low. Moreover, recent studies in remote cultures found no facial configuration to be specific of a given emotion, even though individuals could infer some social meanings from facial expressions (e.g., Trobriand Islanders labeled the proposed facial configuration for fear as signaling intent to attack). Thus, these findings do not seem to support the reliability, specificity, generalizability, and validity criteria to establish a direct relationship between facial expressions and emotional states.
Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements [LISA FELDMAN BARRETT (Department of Psychology, Northeastern University; Department of Psychiatry, Massachusetts General Hospital; Athinoula A. Martinos Center for Biomedical Imaging), RALPH ADOLPHS (Division of Humanities and Social Sciences, California Institute of Technology), STACY MARSELLA (Department of Psychology, Northeastern University; College of Computer and Information Science, Northeastern University; Institute of Neuroscience & Psychology, University of Glasgow), ALEIX M. MARTINEZ (Department of Electrical and Computer Engineering and Center for Cognitive and Brain Sciences, The Ohio State University), AND SETH D. POLLAK (Department of Psychology, University of Wisconsin–Madison)/Psychological Science in the Public Interest (Volume 20, Number 1)]
Emotion-detection applications built on outdated science, report warns [Association for Psychological Science/Eurekalert]
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