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Understanding the Concept of Artificial Emotional Intelligence

We, humans, are an emotional bunch. This means a lot of what we do and how we do it is based on our emotional state. This has a major impact on the activities performed and the eventual result. For a person who had a hearty breakfast after a good night’s sleep is going to be […]


Published By - Kelsey Taylor

We, humans, are an emotional bunch. This means a lot of what we do and how we do it is based on our emotional state. This has a major impact on the activities performed and the eventual result.

For a person who had a hearty breakfast after a good night’s sleep is going to be in a good mood. He could ease through his work without breaking much sweat.

But a person who had a bad start to his/her day would be irritable towards everyone. This could hamper his performance throughout the day.

So we can conclude that emotions play a huge role in what we do through the day. It would, thus, be of great benefit if there was some way machines could understand our emotions.

So now, let’s take a look at how machines and specifically artificial intelligence is using human emotion.

What is Artificial Emotional Intelligence?

Artificial Emotional Intelligence or Affective Computing is a subset of the broader Artificial Intelligence unit. It deals with understanding emotions and using them to advantage across applications.

Artificial emotional intelligence deals with measuring human emotion, understanding stimuli, and giving back an appropriate response that will be the aptest for the situation.

Machines understand emotions or emotional states with the help of subtleties in the expressions on human faces. They measure stress or anger with the help of sensors to understand the increased blood pressure of the person.

The process of detecting and recognizing emotions begins with machine learning. Data from passive sensors is gathered about the physical state of the person without any input.

This data is then mapped to the cues that help us interpret emotions in others. Such as a smile might imply happiness or laughter.

Applications of Artificial Emotional Intelligence Across Different Sectors

Applications for artificial emotional intelligence are aplenty. Many industries are already using it in their functions. Some of them are as follows:

Call Center- Improving Customer Experience by Suggesting Appropriate Responses During the Conversation

During any call at a call center, artificial emotional intelligence estimates the mood of the customer on the line. It then accordingly suggests conversation or solution paths to the employee.

This helps the employee navigate the conversation and provide the remedy with much ease. It also ensures that the customer has a satisfactory experience.

Automotive – Making Roads Safer by Giving Warnings in Advance

Manufacturers of self-driving cars are putting artificial emotional intelligence to good use. The software can now roughly calculate the mood of the driver and accordingly adjust the car’s settings. It can detect if the driver is falling asleep and provides an alarm for the same.

Also, drivers who might be arguing with the co-passenger or are sleep deprived are more likely to drive a bit rashly. The car can convey the same to the driver to take safety precautions in such cases.

Marketing and Advertising – Suggesting Content Best Suited to Your Mood

Emotions play a massive role in the marketing and advertising industry. Hence artificial emotional intelligence finds extensive applications in advertising. By figuring the mood or emotional state of the user, certain ads or marketing campaigns can be targeted towards them for a higher impact.

Healthcare – Helping People Who Need Continuous Assistance

Artificial emotional intelligence helps in assistive services such as for people who have autism or dyslexia. Artificial emotional intelligence can judge the mood of the person since emotions of such people are a roller coaster.

Using this information, they can function or learn and perform other activities better.

Also Read- 5 Success Stories of Artificial Intelligence

Real-Life Examples of Artificial Emotional Intelligence

Artificial emotional intelligence is being used in our day-to-day lives as well. Often, we don’t even understand it being used on us unless we are looking for it. Some examples are as follows:

Affectiva

Affectiva is an emotional AI-based company established in 2009. They use the webcam available to track the users’ emotions and moods. They identify the various twitches and subtle changes in micro-expressions for emotion detection.

They do take appropriate permission, though, before using user data and recording through the webcam. Affectiva is then able to help advertisers target more effectively using the emotional quotient of the users.

CrowdEmotion

CrowdEmotion is a London based company that was founded in 2013. The company strives to leverage the technology that uses emotional artificial intelligence.

Their emotional engine helps their clients to recognize and understand human emotions. This enabled them to be able to deliver an experience one step above their peers.

CrowdEmotion’s product, ENGAGE, uses the camera on your computer system or your phone to track your eye movements. The solution is capable of reading your micro-expressions. It then identifies your emotional response to what you are watching or listening to.

NVISO

NVISO uses Artificial Visual Intelligence and deep learning algorithms in their solutions. Their solutions recognize and understand human emotions and over all devices. It is used over various industries including finance, automotive and healthcare.

NVISO trains its solutions by feeding them a large number of datasets. This helps them to detect, identify and interpret behaviors from the images. This makes the solutions capable of adapt to problems and evolve over time with improved accuracy.

These solutions are not just able to understand human emotions but also act in line with the same with the help of emotion analytics.

BeyondVerbal

Beyond Verbal combines AI and voice recognition technologies to detect various health conditions. It does so with the help of voice analysis. They have collaborated with various health institutions to conduct their trials. Their product will enable continuous monitoring of the patient’s health.

Promobot + Neurodata Lab

Neurodata Lab has enabled Promobot to recognize and interpret human emotions.

The autonomous service robot is capable of remembering the people it has interacted with. It is also capable of engaging in human-like conversations. It is capable of working in crowded places as well.

Promobot finds applications in various places such as cinema halls, museums, business centers, and many more. Its increasing number of applications is sure to improve the quality of service. This will, in turn, lead to increased customer loyalty, and better financial performance as well.

A quick comparison of Artificial Intelligence vs. Emotional Intelligence

If we look at the comparison between the two, we can say that neither of them is replaceable. Both have their own set of strengths and weaknesses.

Today artificial intelligence has come a long way to be able to perform a multitude of functions. But without emotional intelligence, it has its shortcomings in some areas. Hence, emotional intelligence helps in fixing specific gaps that exist in artificial intelligence.

With new advances, emotional AI-based machines are able to pick up human emotions. They are probably capable of identifying emotions more accurately and quickly than humans.

At that stage, humans might become dependent on machines for everything. That sounds like a very grey future from a certain point of view, but it is a possibility.

Artificial emotional intelligence upcoming field in artificial intelligence. It will keep on developing as new advances are made.

Experts are on the lookout for new avenues for where it can be used. While the rest are looking for applications and products to further their enterprises.


You May Also Like To Read-

5 Examples of Artificial Intelligence in Decision Making

Kelsey manages Marketing and Operations at HiTechNectar since 2010. She holds a Master’s degree in Business Administration and Management. A tech fanatic and an author at HiTechNectar, Kelsey covers a wide array of topics including the latest IT trends, events and more. Cloud computing, marketing, data analytics and IoT are some of the subjects that she likes to write about.

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