What are the risks of predicting human emotions using artificial intelligence (AI)?


Key takeaways:

  • What are the risks associated with predicting human emotions using Artificial Intelligence? 

We also know AI as machine intelligence. It is a field of computer science that deals with the creation of intelligent machines. Machines that react like humans.

AI, along with ML, applies in many applications. One of the most common applications is emotion detection. But recognizing human emotion is not an easy task.

Be it the human itself or even the modern machines, based on AI. So, there exist some risks of doing so. And that is what I will discuss in this blog. 

So, without further ado, let’s start!

How people feel from inside is never displayed on the outside. So, it is always difficult to read and understand their emotions. A lot of companies use human surveys to do so. But that’s an old technique. 

Today, in the age of AI and ML, we can use one of the most popular Artificial emotional intelligence. It is clear and somewhat biased. This emotional AI technology uses several parameters to read the emotions.

AI

Some parameters are facial expressions, eye movements, voice patterns, etc. The ultimate outcome appears much better than that obtained from surveys. 

The risk of bias in emotional AI

As stated earlier, the results of this emotional AI technology appear biased, sometimes. This is because of the subjective nature of emotions we humans possess. To support my statement, let me give an example. 

A study found that this AI technology assigns negative emotions to certain caste/ethnicities. With the help of AI, it is difficult to extract accurate conclusions. This is because we do not design AI to understand cultural differences in expressing emotions. 

For example, a simple smile may mean something in India and another thing in Japan. This is because of cultural differences between the two countries. Hence, any confusion can lead to wrong decision making. 

In short, emotional bias can immortalize conceptions at an unusual scale. 

How businesses can prevent bias from seeping into common use cases

The following are some ways by which businesses can prevent emotional bias from seeping in. 

  • Understand how emotionally engaged employees are

In business, AI can impact the work allocated to an employee. For example, at first, an employee might find the allocated role most suitable. But, after some new projects, he/she might feel that his/her skills are better when aligned elsewhere. 

Hence, various companies allow each employee to try different roles to find the most suitable one. So, emotional bias leads to the wrong role allocation and decision making.

  • Improve the ability to create products that satisfy the customer’s emotions

Creating a product that excites a particular emotion in the customer is the main aim of product developers. One example of such products is Activa’s Auto AI platform that senses the rider’s emotion(s) and changes the in-cabin environment accordingly. 

Hence, with AI, any service/product can become an adaptive experience. But again, a biased in-cabin environment might misunderstand one’s emotion.

  • Improve tools to measure customer’s satisfaction

Some companies like Cogito use certain tools to help their employees interact better with the customers. The tool’s algorithm helps the employee to handle callers via the company’s app. 

For example, when an angry customer calls to complain about the service, the Cogito’s platform would guide the employee to display sympathy. 

Conclusion 

Hence, emotional AI technology is aimed at offering new metrics to businesses. This improves their relationships with customers and employees. But it is equally important to prevent emotional bias from seeping in.