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Emotional AI: When AI is sensitive towards human emotions, a role beyond understanding

DIGITAL VENTURES January 31, 2019 12:37 AM


Speaking of Artificial Intelligence, we often think of understanding massive data that is beyond human capabilities. However, AI are crossing boundaries to a quite remarkable role which is using AI to understand human behavior via emotional AI. Despite the same AI word in its name, its different concepts and operations are worth noting. Also, its application to various sectors is quite astonishing. What are they? Let’s have a look.



What is emotional AI?

Emotional AI is a technology that aims to use computers to automatically understand emotions, feelings, and habits via all sorts of communication. This includes visually analyzing facial expressions or actions, listening to the tone of voice, and observing the language used to communicate.

Emotional AI combines various technologies such as face recognition to track faces, voice recognition to track sound, and NLP (Natural Language Process) which helps to comprehend the language context. Moreover, psychology needs to be incorporated as it is the foundation of the understanding of a human.



How do emotional AI works?

Emotional AI incorporates technologies in various innovation to track and analyze. These different forms then become a distinctive feature. Emotional AI operates with 3 main approaches as follow:

  • Facial and movement recognition. We normally communicate with language but express feelings with facial expressions and body language. Therefore, emotional AI needs to track and understand different types of human facial reactions and movement to assess the person’s mood and feeling. The technology involved is image recognition that learns through its visual capabilities.
  • Voice and language recognition. In a conversation, we can detect a person’s mood through their tone of voice. Examples are a strong voice when unsatisfied and a softer voice when not confident. Voice recognition is another way for AI to understand human. Here, voice recognition technology is incorporated as it can transform voice to data that computers can understand. Moreover, the choice of words can also tell whether the meaning is stressed or quite relaxed. NLP needs to learn this process.
  • Data management. It is no simple task to fathom the human heart. For AI to understand human, it needs massive data for precise assessment. Here, machine learning comes into play as it can quickly learn big data. This helps the AI to precisely analyze emotions and respond.


Benefiting from emotional AI

Technology development is no buzz without actual applications. Some may have heard that emotional AI only supports service businesses, actually, the concept can also be applied to other sectors as follow:

  • Security. Examining emotions is not limited to the service sector, but it can also track risk-prone behavior that may not be personal matters. An example is with numerous drivers on the highway every day. Here, emotional AI can track risk-prone behaviors such as drowsiness or intoxication before a human begins driving. This can help prevent accidents on the road.
  • Health. Today, health consciousness is not limited to the physical body, but it also relates to mental health. At present, we often encounter patients with stress and depression problems. The number of patients is so high that it exceeds the capability of medical personnel. Therefore, emotional AI that can detect human emotions and diagnose a large number of patients can be part of the assessment and pre-screening process before proceeding on to the next steps of medical care. This will surely be a great solution.
  • Business. The business sector can utilize emotional AI in consumer satisfaction evaluation that can help acquire consumer insights. An example is embedding cameras that use this technology in an advertisement screen. They can assess the behavior of consumers who stop to browse the ad. Another feasible idea is considering the tone of voice of call center users from the hundreds of calls per day and using them to evaluate or improve operations.
  • Initiate emotionally engaged communication. Aside from assessing emotions for various benefits, computers can communicate with emotions in the forms generated by emotional AI. A tangible and existing example is seen today in literary works. At present, startups that recheck language usages like Grammarly and Textio are using AI to verify sentences, meanings, and choice of words. These processes can’t succeed if they are unable to comprehend the emotions that are communicated through the text.


Although doors are open for innovation development and have made computers understand human emotions, there are still many concerns. This is especially true for the learning of human behavior and emotions which is related to personal rights. We have more stories regarding AI. Follow us for more updates.

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