UPFRONT | News and events EXCELLENCE How we see others’ emotions depends on our pre-conceived beliefs how we see emotions on another person’s face de-pends on our pre-conceived views of how we understand these emotions, researchers at New York University have found. Their study, which appears in the journal Na-ture Human Behaviour , makes new insights into how we recognize facial expres-sions of emotion, which is critical for successful inter-actions in business, diplo-macy, and everyday social exchange. The study, conducted with Jeffrey Brooks, an NYU doctoral student, involved a series of experiments in which subjects were asked about their conceptualiza-tions of different emotions. This was used to estimate how closely related different emotions were in a subject’s mind. For instance, some people might think anger and sadness are more similar emotions if they conceptu-ally associate both these emotions with actions such as crying and slamming your fist on a table; other people might think they’re entirely different emotions because they associate the two emo-tions as feeling completely different and resulting in different actions. Specifi-cally, subjects were assessed in how similarly they held different pairs of the follow-ing emotions in thier mind: anger, disgust, happiness, fear, sadness and surprise. These six emotions have long been argued by some scientists to be universal across cultures and generally hard-wired in humans. Overall, the experiments showed that when individuals believed any two emotions were conceptually more similar, faces they saw from those categories of emotions were visually per-ceived with a corresponding similarity. In another experiment, a technique known as ‘reverse correlation’ was used to vis-ualize the six different emo-tions in the mind’s eye of a subject. The researchers started with a single neutral face and created hundreds of different versions of this face that were overlaid with different patterns of random noise. The noise patterns create random variations in the face’s cues; for example, one version might look more like it is smiling rather than frowning. On each trial of the experiment, subjects were presented with two different versions of this face and decided which of the two appeared more like a specific emotion (e.g., an-ger) – even though in reality it was only the noise pattern creating any difference in the two versions’ appear-ance. On the basis of the noise patterns a subject chose, an average facial “prototype” for each of the six emotions could be visu-alized – serving as a kind of window into the mind’s eye of a subject. Converging with the mouse-tracking results, when any two emotions were conceptually more similar in a subject’s mind, the images of those two visualized facial prototypes physically resembled one another to a greater extent. For instance, if a study subject viewed anger and disgust to be conceptually more similar, the visualized images of what an angry face and a disgusted face look like to that subject had a greater physical resemblance. “The findings suggest that how we perceive facial ex-pressions may not just reflect what’s in the face itself, but also our own conceptual understanding of what the emotion means,” explains Jonathan Freeman, the pa-per’s senior author. “For any given pair of emotions, such as fear and anger, the more a subject believes these emo-tions are more similar, the more these two emotions visually resemble one an-other on a person’s face. The results suggest that we may all slightly differ in the facial cues we use to understand others’ emotions, because they depend on how we conceptually understand these emotions.” The study’s results con-trast with classic scientific theories of emotion that as-sume each emotion has its own specific facial expres-sion that humans universally recognize. Based on this view, the same exact facial expression, such as a scowl-ing face for anger, should always elicit a perception of anger, and our personal-ly-held beliefs about what constitutes “anger” should not affect the process. The findings, Freeman observes, may have implica-tions for artificial intelli-gence and machine learning for facial emotion recogni-tion, and other computer-vision and security applications. — New York University MARKETING 5 tips to manage customer info here are five ways you can responsibly collect and manage your customer’s information. 1. Compliance. Beyond local and federal laws, many industries have their own codes of conduct regarding customer data. These can cover everything from how data is collected to what incentives can be offered in return for sharing such data. This should be your starting point. 2. Gather only what you need. The more information you ask from customers, the less likely they are to give it to you. Also, more infor-mation means more resources needed to manage it. 3. Storage. While it can be ar-gued that no data is truly safe, you can still reduce the chances of it being hacked. Start with an estab-lished, offsite data management company. Not only will it be auto-matically backed up and physical-ly safe from theft, but many secu-rity features come standard. 4. Internal policies and guide-lines. The weakest link in any secu-rity system is the human one. Beyond making sure you control who has access to the data, it is also important to establish clear policies and guidelines. This will ensure the data is used in accord-ance with local laws while encom-passing corporate and social re-sponsibility. Sharing these policies with the public is an important part of building trust. 5. Transparency. People don’t mind sharing personal data if they feel doing so will benefit them. So let them know what the deal is. What will it be used for? Will it be shared? What will the customer get out of it? Can they have the data removed if they wish? These are all questions who’s answers should be honest and accessible. — Marc Gordon, marcgordon.ca www.canadianchiropractor.ca 6 Canadian Chiropractor September 2018
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