A New Artificial Intelligence Frontier: Understanding Emotion


Human nature is a baggy, capacious concept, and one that technology has altered and extended throughout history. Digital technologies challenge us once again to ask what place we occupy in the universe: what it means to be creatures of language, self-awareness and rationality.

Our machines aren’t minds yet, but they are taking on more and more of the attributes we used to think of as uniquely human: reason, action, reaction, language, logic, adaptation, learning. Rightly, fearfully, falteringly, we are beginning to ask what transforming consequences this latest extension and usurpation will bring.

Dr. Tom Chatfield, Lecture for The Oxford Research Center in the Humanities, January 2016

Artificial intelligence (AI) promises to make work and life more productive. But to do so, AI needs to better understand humans, which are the most complex organisms on earth. A significant element of AI’s limitations, to date, is understanding humans and, more specifically, human emotion. There is no scientific consensus on the definition for emotion, but many experts agree that emotion “influences thinking, decision-making, actions, social relationships and well-being.”

Accelerated access to data (primarily social media feeds and digital video), cheaper compute power, and evolving deep learning, combined with natural language processing (NLP) and computer vision, are enabling technologists to watch and listen to humans with the intention of analyzing their sentiments and emotions. A better understanding of emotion will enable AI technology to create more empathetic customer and healthcare experiences, drive our cars, enhance teaching methods, and figure out ways to build better products that meet our needs.

Emotion and sentiment analysis is complex because emotion is complex and not very well understood. Emotion can be deceptive and expressed in multiple ways: in our speech intonation, the text of the words we say or write, and in our facial expression, body posture, and gestures. These factors create variables in emotion analysis confidence scoring that must be overcome for most sentiment and emotion analysis use cases to come into full bloom.

Despite these challenges, the market for sentiment and emotion analysis use cases has begun to expand. Tractica has identified seven use cases where significant direct software revenue will be generated through 2025: customer service, product/market research, customer experience, healthcare, automotive, education, and gaming

Tractica defines sentiment and emotion analysis as forks of emotion analysis, where sentiment discerns at a high level among positive, negative, and neutral categories, and where emotion discerns at a minimum of six specific emotions.

Today’s Sentiment-Emotion Analysis Market

An immature ecosystem for sentiment and emotion analysis has formed, made up of research scientists in the fields of AI, mental health and medicine; and leading e-commerce merchants, market research specialists, automated customer service vendors, AI platform players, and a small but impressive number of computer vision and NLP-based solution startups. There has been commercialization of sentiment analysis for market/product research, which is expanding beyond simpler positive/negative/neutral analysis to more nuanced emotion analysis. Hyper-competitive markets and high customer expectations (set by players like Amazon, Apple, and JetBlue) are evolving business strategies to where companies are looking to differentiate on customer experience. To do so, innovators are using real-time emotion analysis to help guide both human and automated customer service and transactional interactions. In the lab, it is early days for leveraging emotion analysis in healthcare coaching, medical diagnosis, education, and autonomous vehicle applications.

Market Drivers

There are two primary market forces driving sentiment and emotion analysis today: the need and desire to humanize digital communications, and the evolving thinking about the importance of emotion to customer experience.

Empathy Humanizes Digital Communications

Studies have shown that digital communications are eroding our ability to empathize with others. As digital communications become even more prevalent, expressed empathy becomes more important within those communications.

A 2010 study from the University of Michigan showed that college students over a 30-year period had a 40% decrease in empathetic capabilities, with the sharpest drop after the year 2000, which is considered the year of the dawn of digital communications.

There are three core components of empathy: affective understanding, emotion contagion, and perspective taking. Two of these, affective understanding and perspective taking, were found to have been eroded the most by digital media.

  • Affective Understanding: The skill of knowing how others are feeling is only acquired by practice and life experience and is a continuous process of interpersonal communication. Most of this communication is non-verbal, such as facial expressions, gestures, and tone of voice and posture. This means that a great deal of the cues needed to understand emotions are left out of text-based digital communications.
  • Cognitive Perspective Taking: This is the skill of theoretically walking a mile in someone else’s shoes. As a learned behavior, cognitive perspective taking is widely acknowledged to improve relationship satisfaction, compassion, and gratitude, and a sense of social belonging. Digital media, particularly social media, has eroded this component of empathy the most. Social media’s curated sources of information are tailored to individual interests and beliefs, limiting broader points of view.

One area where empathy will become increasingly important is chatbots. Tractica estimates that the market for enterprise virtual digital assistants, primarily chatbots engaged in customer service, e-commerce, and healthcare, will grow to more than $7 billion in 2025. Customer service and healthcare interactions require a high degree of empathy. A key element to success for these chatbots will be their ability to understand human emotions within a conversation and take appropriate action.

Emotion Is the Key to Customer Experience

In the competitive marketplace, companies of all kinds are increasingly focused on making customer experience their competitive differentiator. More and more, companies are finding that the customer experience is not just about customer satisfaction, but more about the customer’s emotional connection.

Emotional Motivators

(Source: HBR.org)

Understanding emotion is important to customer experience because emotion is an integral part of decision making. In a blog post, Clarabridge product manager Ellen Falci wrote, “A few years ago, neuroscientist Antonio Damasio studied individuals with damage to the emotional center of the brain. He found that, while these individuals seemed typical in many ways, they were unable to feel emotions and or to make decisions. They could describe their own actions but they were unable to make even the most minor decisions. Their inability to evaluate the pros and cons using emotional weight as a barometer paralyzed their capacity to choose one option or the other.”

Emotion intelligence player Motista has found that emotional connection has led to significantly higher value in consumer financial services. In its white paper, the company found that based on data from 60,000 retail bank customers, “Emotionally Connected customers hold 20 percent more products with their banks than do customers who say they are ‘Highly Satisfied,’ have a 78 percent lower attrition rate, and consider their bank as their primary bank 32 percent more often. As a result, Emotionally Connected customers produce nearly six times the lifetime revenue of Highly Satisfied customers.”

In a blog post in June of 2017, Cogito chief executive officer (CEO) Josh Feast wrote, “Leading companies and customer experience analysts have discovered that a customer’s emotional experience with a company is the most important component in developing a relationship. In fact, according to noted customer experience expert Bruce Temkin’s extensive research, customers who experience an interaction in which a good emotional connection is developed are 12 times more likely to recommend that company to a friend. There is significant value in fostering emotional intelligence within customer facing organizations. Customers that feel good about an interaction with a company are 5 times more likely to forgive a mistake, and 6 times more likely to buy additional goods or services. Accenture estimates that 1.6 trillion dollars are available in the U.S alone from customers choosing to switch providers each year.”

While these factors are driving the market, there are challenges to productizing sentiment and emotion analysis. Look for details on the market barriers in an upcoming post.

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