By Natalia Modjeska, MBA, PhD, helps organizations make sense of AI/ML. Recently I had the opportunity to attend the inaugural Emotion AI Conference, organized by Seth Grimes, a leading analyst and business consultant in the areas of natural language processing (NLP), text analytics, sentiment analysis, and their business applications. The conference was attended by about 70 people (including presenters and panelists) from industry and academia in the US, Canada, and Europe. Given the conference topic, what is emotion AI, why is it relevant, and what do you need to know about it? Read on to find out (warning: this is a long-ish article), but first, some background. We humans are highly emotional beings, and emotions impact everything we do, even if we are not, for the most part, aware of it.

When we think of robots, we often think of mechanical objects that repeatedly carry out simple tasks or serve to the more basic roles in society and while the media may have portrayed robots that could mimic human behavior from movies such as Big hero 6 or Wall E, the idea of a robot not only interacting but understanding the nuances of human behavior seemed almost impossible. This is where Rana el Kaliouby comes in, an academic who studied at Cambridge and MIT, and spent her career tackling an increasingly important limitation of technology - that computers do not understand humans, became the co founder of a Boston based start up called Affectiva, and has been working in the dynamic field of Human Robot Interaction (HRI) for more than 20 years. In a recent interview, Ms Kaliouby stated "Technology today has a lot of cognitive intelligence, or IQ, but no emotional intelligence, or EQ",and goes on to say, "We are facing an empathy crisis. We need to redesign technology in a more human-centric way." While this isn't a main concern of AI that performs data driven, logical tasks such as data processing, but it does become a bigger concern when the AI is in contact with clients, whether it be an AI receptionist or a robot driver. Increasingly, artificial intelligence is being used to directly have contact with humans.

In its annual report, the AI Now Institute, an interdisciplinary research center studying the societal implications of artificial intelligence, called for a ban on technology designed to recognize people's emotions in certain cases. Specifically, the researchers said affect recognition technology, also called emotion recognition technology, should not be used in decisions that "impact people's lives and access to opportunities," such as hiring decisions or pain assessments, because it is not sufficiently accurate and can lead to biased decisions. What is this technology, which is already being used and marketed, and why is it raising concerns? Researchers have been actively working on computer vision algorithms that can determine the emotions and intent of humans, along with making other inferences, for at least a decade. Facial expression analysis has been around since at least 2003.

Artificial intelligence as a discipline consists of hundreds of individual technologies, concepts, and applications. These terms have become increasingly important as STEM education expands and there is a boom in practical household and consumer-facing applications for the technology. Despite that, there is a lack of consistency in how many AI concepts are discussed, not just at the STEM education level, but in popular entertainment, science writing, and even at times in scientific journals. To address this, we need to standardize how we describe AI and its many subsets, and accurately define these terms both in general and specific to individual technologies and applications of those technologies. We discuss some of the most commonly misused and what they really mean.

Artificial intelligence as a discipline consists of hundreds of individual technologies, concepts, and applications. These terms have become increasingly important as STEM education expands and there is a boom in practical household and consumer-facing applications for the technology. Despite that, there is a lack of consistency in how many AI concepts are discussed, not just at the STEM education level, but in popular entertainment, science writing, and even at times in scientific journals. To address this, we need to standardize how we describe AI and its many subsets, and accurately define these terms both in general and specific to individual technologies and applications of those technologies. We discuss some of the most commonly misused and what they really mean.

I'm told I should prepare for the day an artificial intelligence takes my job. This will leave me either destitute and rootless or overwhelmed by a plenitude of time and existential terror, depending on whom you ask. It's apparently time to consider what kind of work only humans can do, and frantically reorient ourselves toward those roles -- lest we be left standing helplessly, as if at the end of some game of robot musical chairs. Emotional labor is a form of work less often considered in these automated future projections. Perhaps this is because the work it takes to smile at a rude customer or to manage their distress is intangible, difficult to quantify and monetize.

When John McCarthy and Marvin Minsky founded Artificial Intelligence in 1956, they were amazed how a machine could perform incredibly difficult puzzles quicker than humans. However, it turns out that teaching Artificial Intelligence to win a chess match is actually quite easy. What would present challenges would be teaching a machine what emotions are and how to replicate them. "We have now accepted after 60 years of AI that the things we originally thought were easy, are actually very hard and what we thought was hard, like playing chess, is very easy" Social and emotional intelligence come almost automatically to humans; we react on instinct. Whilst some of us are more perceptive than others, we can easily interpret the emotions and feelings of those around us.

In a digital world, how do we build empathy into the algorithms that run our lives? Join us for a special virtual briefing hosted by Greg Williams, Editor of WIRED with Rana el Kaliouby, co-founder and CEO of Affectiva, and author of'Girl Decoded' as they discuss how to bring emotional intelligence to technology during a global health emergency, such as the COVID-19 outbreak in 2020. Even before the coronavirus pandemic began earlier this year, the world had already moved to an increasingly digital setting. Emails, texts and social media interactions were fast-becoming the norm over physical meetings. However, words convey only a fraction of the true meaning behind a message, and as a result, we are missing key physical, non-verbal cues that give us a more complete understanding of each other.

ABSTRACT Mirror Ritual is an interactive installation that challenges the existing paradigms in our understanding of human emotion and machine perception. In contrast to prescriptive interfaces, the work's real-time affective interface engages the audience in the iterative conceptualisation of their emotional state through the use of affectively-charged machine generated poetry. The audience are encouraged to make sense of the mirror's poetry by framing it with respect to their recent life experiences, effectively'putting into words' their felt emotion. This process of affect labelling and contextualisation works to not only regulate emotion, but helps to construct the rich personal narratives that constitute human identity. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.

If anything can supersede the hype around artificial intelligence (AI) than it is probably Emotion AI, the irony is that the latter is the subset of AI itself. The hype around emotion AI revolves around the excitement of witnessing the mass infiltration of machines into complex world of human emotions. For too long machines have been considered as a beast that can interpret & simplify complex data but miserably falls short of replicating the same magic in the area of human emotion. However, this hypothesis and assumption is now being challenged by artificial intelligence. Emotion Ai is essentially one of emerging areas of AI where machines seek to analyze and comprehend human emotions by judging facial expressions, body language, gestures, voice tone so and so forth.