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Emotion recognition is a hot new area, with companies peddling products that claim to be able to read people鈥檚 internal emotional states, and AI researchers looking to improve computers鈥� ability to do so. This is done through , , , , and remote measurement of like pulse and breathing rates. Most of all, though, it鈥檚 done through analysis of facial expressions.

A new , however, strongly suggests that these products are built on a bed of intellectual quicksand.

The key question is whether human emotions can be reliably determined from facial expressions. 鈥淭he topic of facial expressions of emotion 鈥� whether they鈥檙e universal, whether you can look at someone鈥檚 face and read emotion in their face 鈥� is a topic of great contention that scientists have been debating for at least 100 years,鈥� Lisa Feldman Barrett, Professor of Psychology at Northeastern University and an expert on emotion, told me. Despite that long history, she said, a comprehensive assessment of all the emotion research that has been done over the past century had never been done. So, several years ago, the Association for Psychological Science brought together five distinguished scientists from various sides of the debate to conduct 鈥渁 systematic review of the evidence testing the common view鈥� that emotion can be reliably determined by external facial movements.

The five scientists 鈥渞epresented very different theoretical views,鈥� according to Barrett, who was one of them. 鈥淲e came to the project with very different expectations of what the data would show, and our job was to see if we could find consensus in what the data shows and how to best interpret it. We were not convinced we could, just because it鈥檚 such a contentious topic.鈥� The process, expected to take a few months, ended up taking two years.

Nevertheless, in the end, after reviewing over 1,000 scientific papers in the psychological literature, these experts came to a unanimous conclusion: there is no scientific support for the common assumption 鈥渢hat a person鈥檚 emotional state can be readily inferred from his or her facial movements.鈥�

The scientists conclude that there are three specific misunderstandings 鈥渁bout how emotions are expressed and perceived in facial movements.鈥� The link between facial expressions and emotions is not reliable (i.e., the same emotions are not always expressed in the same way), specific (the same facial expressions do not reliably indicate the same emotions), or generalizable (the effects of different cultures and contexts has not been sufficiently documented).

As Barrett put it to me, 鈥淎 scowling face may or may not be an expression of anger. Sometimes people scowl in anger, sometimes you might smile, or cry, or just seethe with a neutral expression. Also, people scowl at other times 鈥� when they鈥檙e confused, when they鈥檙e concentrating, when they have gas.鈥�

The scientists conclude:

These research findings do not imply that people move their faces randomly or that [facial expressions] have no psychological meaning. Instead, they reveal that the facial configurations in question are not 鈥渇ingerprints鈥� or diagnostic displays that reliably and specifically signal particular emotional states regardless of context, person, and culture. It is not possible to confidently infer happiness from a smile, anger from a scowl, or sadness from a frown, as much of current technology tries to do when applying what are mistakenly believed to be the scientific facts.

This paper is significant because an entire industry of automated purported emotion-reading technologies is quickly emerging. As we wrote in our recent paper on 鈥�Robot Surveillance,鈥� the market for emotion recognition software is forecast to reach at least $3.8 billion by 2025. Emotion recognition (aka 鈥渁ffect recognition鈥� or 鈥渁ffective computing鈥�) is already being incorporated into products for purposes such as marketing, robotics, driver safety, and (as we recently wrote about) audio 鈥渁ggression detectors.鈥�

Emotion recognition is based on the same underlying premise as polygraphs aka 鈥�lie detectors鈥�: that physical body movements and conditions can be reliably correlated with a person鈥檚 internal mental state. They cannot 鈥� and that very much includes facial muscles. What is true of facial muscles, it stands to reason, would also be true of all the other methods of detecting emotion such as body language and gait.

The belief that such mind reading is possible, however, can do real harm. A jury鈥檚 cultural misunderstanding about what a foreign defendant鈥檚 facial expressions mean can lead them to , for example, rather than prison. Translated into automated systems, that belief could lead to other harms; a 鈥渟mart鈥� body camera falsely telling a police officer that someone is hostile and full of anger could contribute to an unnecessary shooting.

As Barrett put it to me, 鈥渢here is no automated emotion recognition. The best algorithms can encounter a face 鈥� full frontal, no occlusions, ideal lighting 鈥� and those algorithms are very good at detecting facial movements. But they鈥檙e not equipped to infer what those facial movements mean.鈥�