What is It? How Can a Machine Exhibit It? "It's about thinking. The main theory is that emotions are nothing special. Each emotional state is a different style of thinking. So it's not a general theory of emotions, because the main idea is that each of the major emotions is quite different. They have different management organizations for how you are thinking you will proceed."
"Because the main point of the book [The Emotion Machine] is that it's trying to make theories of how thinking works. Our traditional idea is that there is something called 'thinking' and that it is contaminated, modulated or affected by emotions. What I am saying is that emotions aren't separate."
– Marvin Minsky. The Emotion Machine, book and draft, 2006.
Then Alexa takes over basic household functions. And now a robot may be conducting your job interview. That's right--portions of corporate America are now using artificial intelligence ("AI") to conduct interviews of job applicants. How does this work, what are the risks and has there been a legislative response? And how would the Luddites respond to this?
As new technologies automate more traditional and routine tasks, executives and employees recognize that emotional intelligence (EI) skills – such as self-awareness, self-management, social awareness and relationship management – will be a key requisite for success in the years to come. While demand for EI skills is set to increase by six times in the next 3-5 years, recruitment and training in this area has mostly failed to adapt. This is set to leave many companies unable to reap the benefits EI offers in terms of employee satisfaction, revenue generation, lower attrition and cost reductions. The "Emotional intelligence – the essential skillset for the age of AI" report from the Capgemini Research Institute provides a global look at how companies view EI and recommends that they combine technology with the talent to develop relevant skills among their employees. Executives said employees need to develop EI skills so they can adapt to more client/person-facing roles (76%) and take on tasks requiring EI skills that cannot be automated (also 76%) such as empathy, influence and teamwork.
Customer experience is a critical asset in maintaining customer loyalty for brands, and AI technology combined with data analytics may be the key to keeping consumers engaged in a crowded market, writes, Cris Kuehl, VP of Analytics and Client Insights, Sitel Group. Gen Z is a business opportunity you can't afford to miss. As 40% of the population commanding upwards of $40 billion in spending power, modern marketers need to build compelling strategies to engage with Gen Z. Nearly a third (32%) of customers say they would stop doing business with a brand after only one bad experience and 73% point to experience as an important factor when deciding on a purchase. Customers also aren't shy in spreading the word about their bad experiences – in fact, 30% would write a negative review of a brand online to prevent others from shopping with the brand. All of this said, there's no denying that customer experience (CX) is an important element of any business, but for consumer brands in particular there's an added element of risk involved as customer loyalty is at stake.
Companies have historically used focus groups and surveys to understand how people felt. Now, emotional AI technology can help businesses capture the emotional reactions of both employees and consumers in real time -- by decoding facial expressions, analyzing voice patterns, monitoring eye movements, and measuring neurological immersion levels, for example. The ultimate outcome is a much better understanding both of workers and customers. But, because of the subjective nature of emotions, emotional AI is especially prone to bias. AI is often also not sophisticated enough to understand cultural differences in expressing and reading emotions, making it harder to draw accurate conclusions.
Until recently, technology was somewhat limited in terms of its ability to sense and adapt to human emotions and reactions. Our apps, devices and advanced AI systems have lots of cognitive intelligence, but no emotional intelligence. As such, transactions between humans and machines are relatively superficial and often ineffective. But over the last few years, Affectiva created never-before-seen technology: software that identifies complex human emotional and cognitive states, by analyzing people's faces and voices. Essentially, we infused AI with EI (emotional intelligence)--allowing for much more productive, persuasive interactions between tech and humans. This was a brand-new category that hadn't yet been defined in AI. We coined it "artificial emotional intelligence," or "Emotion AI." As a result, our challenge was to introduce the tech and establish a major footprint for it--as well as our brand--in the AI industry.
We have known for years how much EI matters. Have a look at recent data in this article written by our founder Dr. Margareta Sjolund: There is no question that companies and organizations can become more successful by measuring and developing the Emotional Intelligence (EI) of their leaders and employees. The United Nations hosted a conference in May 2019 on EI as a tool for conflict resolution, Human Capital Institute presented a study on the importance of EI for leadership development and further research shows EI as a key to survival when robots and AI take over manual jobs, rendering them obsolete. AI increasingly takes over routine jobs and leads to significant changes in the workplace for both individuals and organizations. Jobs disappear and new jobs and new roles are created.
About 87% of marketing organizations have already started using some level of personalization. By 2024, AI identification of emotions is expected to influence more than 50% of online advertisements globally. Gartner has confirmed that AEI is among the key technology trends that are expected to witness tremendous growth in the next five years. Computer vision allows AI to interpret and manipulate physical environments, which is one of the key technologies used for emotion recognition. Artificial Emotional Intelligence (AEI) will sense customer emotions, based on which companies can influence buying decisions.
Affective computing could cause some angst, but it must be developed with privacy policies foremost. Given the amount of data available to the world's tech giants-- whether with the individual's implicit knowledge or not-- companies have immense analytical power. Thanks to its users telling the platform more or less everything about themselves, Facebook can essentially predict its users' future. But, regardless of how many personal data and browsing data we choke up to the digital realm, so far our real thoughts, feelings, and emotions are still private to ourselves-- we hope at least. Enter emotional analytics, otherwise known as "affective computing", but so far-- thanks to the prevalence of data consent processes-- use cases are more fascinating than sinister.