Emotion AI: Can Technology Really Feel?
The relationship between humans and artificial intelligence is complicated.
Artificial intelligence has been developing at an impressive fast pace; its abilities today are inspiring, promising, exciting, but at the same time at certain times daunting.
On one side, these technological solutions are bringing about a revolution like no other in people’s daily lives and business operations alike. It’s design at its core aims to maximize efficiency as much as possible by surpassing the human abilities in different ways to make it easier for individual users and larger entities to streamline their workflow and daily routines.
No doubt, the results that AI’s implementation has been yielding ostensibly positive results. Industries across the spectrum are welcoming AI solutions with arms wide open, hoping for new breakthroughs and positive changes. But, at the same time, a warm welcome isn’t the only reaction this revolution is receiving; it is still enshrouded by a cloud of doubt and fear about how exactly it will redefine the relationship between humans and technology.
Perhaps among the most common questions about AI not about how this technology thinks, but about the technology’s ability to feel and respond to emotion. More specifically, how will emotion — the quality that makes humans so unique — factor into the development and operation of the latest AI solutions?
To be able to answer this and many more questions, let’s take a step back and understand how AI works.
The secret of AI’s power is in pattern recognition and analysis: the system identifies and learns to recognize regularities in data sets, which allows to predict future events, behaviors and patterns based on its analysis of the past ones. This exact ability is what allows AI technologies to emulate the human brain’s workings: after all, we learn based on our past experience as well; AI, though, does it way faster.
Now, imagine if this same mechanism that is usually applied to reason and logic is also used to analyze, recognize and even react to human emotion.
As it turns out, it is not all fictional for AI to be able to interpret human emotion — it’s very much possible today and will only become more accessible in the near future. There is a whole new market out there establishing a strong presence known as “affective computing”, and this market segment is already projected to grow to $41 billion by 2022.
Affective computing technology uses a combination of facial analysis, voice pattern analysis, and deep learning to identify, track, and analyze human emotions. No wonder the corporate giants of the tech world today have made definite steps towards establishing a strong presence in this new market.
Affective computing unlocks many new doors for both individual users and corporations are numerous; one of the more common practices of this type of technology today is the combination of emotional intelligence (through emotion AI) with the more traditional logical AI data analytics to establish deeper and more personal relationships between companies and their customers, making each on- and offline interaction more meaningful and fostering loyalty between the two sides.
Now, there are already three major categories of emotion AI technology in implementation today, based on how they interact with humans and factor emotion into their analytical algorithms. This sort of categorization allows to get a step closer to answering the burning question about where emotion AI is taking the traditional relationship between humans and technologies.
The first category is comprised of the solutions that can recognize human emotions when interacting with users and factors them into their analysis and decision-making process; however, they do not react or recreate the emotion in any way. Even if this sounds complicated, chances are, you have already interacted with this sort of technology without even realizing it. Remember the customer service calls and chats where the automated response guides you through the menu and connects you to a representative? These are conversational IVRs and chatbots that help them navigate to the necessary department, menu options, or even a guide you through your customer service journey based on your reactions as a customer.
At the end of the day, this category’s solutions are the technologies as we know them; while they take into account the customer emotion fluctuations during the interactions and decision-making, the machine is just that — a machine.
The solutions in the second category takes the relationship between humans and technology a step further by using emotion analysis to help users navigate their daily lives for their own benefit. Emotion-sensing wearable devices are the epitome of such technology, helping the users are devices helping users with mental and physical health, stress, and other conditions. The relationship in this case keeps the user in charge at all times again, while the technology is a subject adjusting to the unique needs and situation of each user to guide them towards personal growth and overall well being.
The last (and also improbable-sounding) category is perhaps the root cause of all the questions and uncertainty surrounding the development of AI. It includes technologies that begin to blur the line between technology and humans; technologies that are the more advanced versions of Alexa and Siri; technologies that react and respond appropriately to humans after identifying the feelings they are experiencing. These technologies, human-made but aspiring to be human-like, can easily become a user’s friend, helper, or confidante.
Emotion AI is, no doubt, a very controversial topic as it is just making its way into individual users’ lives and corporate infrastructures. And with any groundbreaking innovation, there is a combination of cautious welcome and fear in the air about where developments such as “feeling” and “sensing” technologies can take us. As with everything, time will show what the turnout will be in the near future; but as of right now, the key progress is to realistically assess the benefits AI offers and the questions it raises, and to accept change without allowing the sheer number of new opportunities to blind us.
