Tears from pain, laughter, or anger are very vivid expressions of emotion. They influence our behavior and can be seen as a symptom or predictor of extreme despair. New artificial intelligence technologies can recognize such emotions and use information about the appearance of tears for different purposes. Already, this technology is opening up new opportunities in health care, and enterprising businessmen are thinking about how they can use it to improve their marketing strategies.

AI technology that works with emotions, including tears, is called emotional artificial intelligence. It can be characterized as a separate part of AI, which is essentially a broad term that encompasses many machines that reproduce the way people think. Emotional AI is capable of perceiving human emotions, understanding them, and responding to them in a certain way with a modulated response.

If a machine learns to perceive people’s facial expressions, see tears, and sense their emotional state, it opens up incredible possibilities for interaction. Visual perception can be complemented by auditory perception; tiny speakers can capture the intonation of a person’s voice and recognize how it correlates with the emotion reflected on the face. Machines can analyze this data, capturing the subtleties of micro-expressions that can happen too quickly and imperceptibly for humans.

The ability to perceive tears and the emotions that caused them is simply invaluable for the field of healthcare. Such data could prove very useful for diagnosing mental illnesses and monitoring mental health. Machines that perceive tears and accompanying emotions can also determine how critical a patient’s condition is, and how quickly they need to receive medical care.

Emotional AI can be used in applications to monitor stress levels, in which case it will read information about the emotional state of users and improve coping skills in stressful situations. And if necessary, the application will signal that it is time for the user to seek more specialized help before it is too late.


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