Many people get frustrated with technology when it malfunctions or is counterintuitive. The last thing people might expect is for that same technology to pick up on their emotions and engage with them differently as a result.
All of that is now changing. Computers are increasingly able to figure out what we’re feeling—and it’s big business.
A recent report predicts that the global affective computing market will grow from $12.2 billion in 2016 to $53.98 billion by 2021. The report by research and consultancy firm MarketsandMarkets observed that enabling technologies have already been adopted in a wide range of industries and noted a rising demand for facial feature extraction software.
Affective computing is also referred to as emotion AI or artificial emotional intelligence. Although many people are still unfamiliar with the category, researchers in academia have already discovered a multitude of uses for it.
At the University of Tokyo, Professor Toshihiko Yamasaki decided to develop a machine learning system that evaluates the quality of TED Talk videos. Of course, a TED Talk is only considered to be good if it resonates with a human audience. On the surface, this would seem too qualitatively abstract for computer analysis. But Yamasaki wanted his system to watch videos of presentations and predict user impressions. Could a machine learning system accurately evaluate the emotional persuasiveness of a speaker?
Yamasaki and his colleagues came up with a method that analyzed correlationsand “multimodal features including linguistic as well as acoustic features” in a dataset of 1,646 TED Talk videos. The experiment was successful. The method obtained “a statistically significant macro-average accuracy of 93.3 percent, outperforming several competitive baseline methods.”
A machine was able to predict whether or not a person would emotionally connect with other people. In their report, the authors noted that these findings could be used for recommendation purposes and also as feedback to the presenters, in order to improve the quality of their public presentation. However, the usefulness of affective computing goes far beyond the way people present content. It may also transform the way they learn it.
Researchers from North Carolina State University explored the connection between students’ affective states and their ability to learn. Their software was able to accurately predict the effectiveness of online tutoring sessions by analyzing the facial expressions of participating students. The software tracked fine-grained facial movements such as eyebrow raising, eyelid tightening, and mouth dimpling to determine engagement, frustration, and learning. The authors concluded that “analysis of facial expressions has great potential for educational data mining.”
This type of technology is increasingly being used within the private sector. Affectiva is a Boston-based company that makes emotion recognition software. When asked to comment on this emerging technology, Gabi Zijderveld, chief marketing officer at Affectiva, explained in an interview for this article, “Our software measures facial expressions of emotion. So basically all you need is our software running and then access to a camera so you can basically record a face and analyze it. We can do that in real time or we can do this by looking at a video and then analyzing data and sending it back to folks.”
The technology has particular relevance for the advertising industry.
Zijderveld said, “We have products that allow you to measure how consumers or viewers respond to digital content…you could have a number of people looking at an ad, you measure their emotional response so you aggregate the data and it gives you insight into how well your content is performing. And then you can adapt and adjust accordingly.”
Zijderveld explained that this is the first market where the company got traction. However, they have since packaged up their core technology in software development kits or SDKs. This allows other companies to integrate emotion detection into whatever they are building.
By licensing its technology to others, Affectiva is now rapidly expanding into a wide variety of markets, including gaming, education, robotics, and healthcare. The core technology is also used in human resources for the purposes of video recruitment. The software analyzes the emotional responses of interviewees, and that data is factored into hiring decisions.
Richard Yonck is founder and president of Intelligent Future Consulting and the author of a book about our relationship with technology. “One area I discuss in Heart of the Machine is the idea of an emotional economy that will arise as an ecosystem of emotionally aware businesses, systems, and services are developed. This will rapidly expand into a multi-billion-dollar industry, leading to an infrastructure that will be both emotionally responsive and potentially exploitive at personal, commercial, and political levels,” said Yonck, in an interview for this article.