Emotion Analytics: Can Robots Understand your Feelings?

Artificial Intelligence has excelled in making decisions like humans and has been successful in replicating them in an astonishing way.

Machines have been transformed and made humanly powerful, but here a significant question arises that are they made emotionally intelligent?

Emotions come naturally to humans as per the status of circumstances and the environment surrounding them. We can intercept the emotions and feelings of those around us and sometimes even by looking at the people we can be perceptive and make out how they feel or are going to react.

The base-level intelligence in a normal individual is partly gifted at birth and is partly learned gradually, which tells them how to behave and respond in both certain and uncertain situations that come across.

Making this automatic understanding, learn to the machines is not less than a challenge for tech experts where they have to let machines think, react and even feel like humans to do justice to the ever-new revolutionizing concept.

All eyes are on Artificial Intelligence technology!

Emotional Analytics

Analysis of emotions allows Artificial Learning to analyze the feelings of a human being either by their gestures, their words, or their tone of voice. Thus, they can take actions as appropriate, make the interaction with a chatbot more friendly or determine if the person is near or far from making a purchase.

Evolution has led human beings on an amazing path that has not been reached by any other being – that we know of. The brain is the pride of our species and yet, despite this, from all our reasoning, a very important part of our actions are governed by emotions.

Obviously, emotions are not the only thing that leads us to make decisions. There are other aspects of capital importance such as utility or cost but emotions always carry much greater weight than we think of.

What can AI do with our Emotions?

If you have ever had a serious problem with a large company and trying to solve it, you would have gone from phone to phone, window to window without anyone giving the slightest of empathy and understanding to your situation.

You would have experienced the feeling of dealing with robots without feelings.

If you’ve been through it, you can probably get an idea of one of the points in which emotion analytics can help: something as simple as making the deal with the company more friendly, significantly improving the final experience. You can even detect psychological problems before they become serious.

In recent years we have the proliferation of chatbots. Currently, we can find them on many websites where they answer questions or help us make a reservation. Thanks to the interaction with natural language, they could deduce how close the customer is to the purchase- if it is clear to them or if they are just browsing, or in the investigation phase- and adjust to the needs of each situation.

[Prefer Reading: ”How Natural Language Processing Aids Sentiment Analysis?”]

The Difficulties of Emotion Analytics

Natural language processing is one of the primary technologies used that emotion analytics support. Nevertheless, trying to discern feelings only through words is tremendously complicated since it neglects the entire message conveyed by a non-verbal language.

“Words contain approximately 7% of the message you want to transmit.”

So can we trust that the data that is input to a cognitive machine will output the correct emotion as felt by the individual in front of it?

Companies have deduced many ways and algorithms which promise that they can reliably determine one’s emotion based on facial expressions alone, but are they so proficient to distinguish between anger and scowl? As they fall in the same category but are not the same.

To a certain extent, AI-powered tools can make a difference in unique expressions but the same is not true for detecting emotions as they can be expressed in a multitudinal variety of ways which makes it hard to recognize how someone feels extracting data from a set of facial movements.

Lisa Feldman Barrett, a psychology professor at Northeastern University says, “People scowl less than 30% of the time when they are angry. So scowl is not the expression of anger, it’s an expression of anger- one among many.”

So what can we now say for the companies who use AI tools to detect your emotions and assure for fair and accurate results.

As the view given by the professor clearly states that common or prototypical expressions might exist, and the communicative power of facial expressions has a significant role play in delivering expected results. On deep scrutinizing, one can also realize that when we see people in person we have so much more information about the context of their emotions than simplistic facial analysis.

What Actually AI Uses to Find Out Any Emotions?

This is where facial recognition comes into play. This does more than just create skins on Snapchat along with biometrics and 3D modelling.

Next, concerning that facial recognition is a simple model to fulfill the motive, there occurred a need to dig deep. Many companies started collecting additional metrics and have launched tools that measure emotions by combining face and speech analysis. Metrics looked upon are gait analysis and eye tracking

By this we can simply infer that the relationship of expressions to emotions is not restricted to only a few aspects and is very complex, nuanced, and not prototypical.

There are already numerous applications that are capable of analyzing a face and its mood.

Clmtrackr is an emotions analysis tool where you turn your webcam and stare into the screen and the program tells you about the emotions you are experiencing along with the proportion of anger, sadness or joy.
Apple brought a company that developed a software named Emotient, in 2016, that could read facial expressions.

Bitext, another project is able to do it from a written text which may be able to analyze, for example, the emotions of those who talk about a brand on social networks.

Vokaturi, is another example which can deduce feelings from a voice.

Machines will Have No Emotions, But At Least They will Adapt

It is tempting to think that if a machine can capture our emotions, it is a little closer to having them. But the answer to the question is a resounding No.

Computers and smart machines are undoubtedly outstanding in processing information and crossing data, which can help them figure out what humans feel and take a course of action accordingly. However, coming to feel is something very far from a machine.

In fact, even we still don’t know what it takes to have emotions

But unless the AI we are interacting with suits our emotion, it will manage to create an illusion of empathy. The analysis of emotions will not only sell for brands to exploit our emotions to sell us things, it will also make our relationship with machines friendlier and warmer in a historical moment in which we will increasingly have more contact with them.

Nevertheless, for now, all this empathy will be a very complex illusion.

Humans are a collection of biological algorithms that have been formed, reformed and reshaped by millions of years of evolution. Certainly, it becomes doubtful that how the non-organic algorithms could replicate or surpass everything that organic algorithms can do in human beings.

We can expect to hear more about emotional AI in the future.

[Prefer Reading: “ AI Robots and their Impact on Human Life.”]

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