Did anyone ever tell you that you wear your heart on your sleeve? It’s a popular expression, but obviously, no one is looking at your sleeve to read your emotions. Instead, we tend to study a person’s facial expressions to “read” their emotions. Most of us think we’re rather good at reading faces, but we couldn’t say exactly how we make our interpretations, and we don’t know whether they are accurate. But what if we could use technology to know how another person is feeling? Would it be ethical to do so in the workplace and then act on our findings? Thankfully, technology is not quite ready to do this.
Face reading is a complex science. Paul Eckman, a noted psychologist, maybe the best human face reader in the world. He has been studying the interpretation of emotions for over 40 years and developed a catalog of over 5,000 muscle movements and their emotional content. His work even
spawned a television series called Lie to Me, in which the main characters analyzed micro expressions—expressions that occur in a fraction of a second—to assist in corporate and governmental investigations. Using Eckman’s Facial Coding System, technology firms like Emotient Inc. have
been developing algorithms to match microexpressions to emotions. These organizations are currently looking for patterns of microexpressions that might predict behavior. Honda, P&G, Coca-Cola, and Unilever have tried the technology to identify the reactions to new products, with mixed results. For one thing, since expressions can change instantly, it is challenging to discern which emotions prevail.
A person watching a commercial, for instance, may smile, furrow his brow, and raise his eyebrows all in the space of 30 seconds, indicating expressiveness, confusion, and surprise in turn. Second, it is difficult to know whether a person will act upon these fleeting emotions. Third, the technology
might misinterpret the underlying emotions or their causes. The potential applications of this technology to the workplace include surveillance, gauging reactions to organization announcements, and lie detection. Cameras could be in every meeting room, hallway, and even on employees’ computer screens. Emotion monitoring could be an announced event—say, every Monday from 8 to 9 a.m.—or random. Monitoring could be conducted with or without the knowledge of employees; for instance, data on the emotional reactions of every employee in an organizational announcement meeting
could be read and interpreted through a camera on the wall. So far, the most reliable workplace application seems to be using technology to capture inconsistencies (lying). Even the pioneer of facial emotion recognition, Ekman, said, “I can’t control usage [of his technology]. I can only be certain that what I’m providing is at least an accurate depiction of when someone is concealing emotion.”
For each usage, there is an ethical consideration and a responsibility, particularly if a manager is going to act on the findings or infer the employee’s future behavior. The fact that the technology has not yet fully evolved for workplace application allows time for ethical guidelines to be developed. Foremost among the ethical concerns is privacy. “I can see few things more invasive than trying to record
someone’s emotions in a database,” said privacy advocate Ginger McCall. Concerns about ethical usage are also highly important if managers use technology to make decisions about employees. For example, what if a manager learns from the software that an employee is unhappy and thus
decides to look for a work reassignment for the employee when actually the employee is unhappy about his spouse? Former U.S. counterterrorism detective Charles Lieberman advises, “Recognize [the technology’s] limitations—it can lead you in the right direction but is not definitive.”
Questions
4-11. What do you think are the best workplace applications for emotion reading technology?
4-12. One corporation has already developed algorithms to match micro-expressions to emotions. What are the likely underlying implications?
4-13. Assuming you could become better at detecting the real emotions of others from facial expressions, do you think it would help your career? Why or why not?
Sources: Paul Ekman profile, Being Human, http://www.beinghuman.org/mind/paul-ekman,
accessed April 17, 2015; E. Dwoskin and E. M. Rusli, “The Technology That Unmasks Your Hidden
Emotions,” The Wall Street Journal, January 29, 2015, B1, B8; and D. Matsumoto and H. S. Hwang, “Reading Facial Expressions of Emotion,” Psychological Science Agenda, May 2011, http://www.apa.org/science/about/psa/2011/05/facial-expressions.aspx.
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