We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Over the past two weeks, emotions have run high around the evolution and use of emotion artificial intelligence (AI), which includes technologies such as voice-based emotion analysis and computer vision-based facial expression detection. Video conferencing platform Zoom came under fire after saying it might soon include emotion AI features in its sales-targeted products. A nonprofit advocacy group, Fight for the Future, published an open letter to the company: It said Zoom's possible offering would be a "major breach of user trust," is "inherently biased," and "a marketing gimmick." Meanwhile, Intel and Classroom Technologies are working on tools that use AI to detect the mood of children in virtual classrooms.

Many AI techniques are being used in organizations, and AI will continue to get sophisticated in the third wave of AI. In the Fourth Industrial Age, human creativity, AI at scale, and Emotion AI will be dominant forces that will shape the digital organizations of the future. What is the Third Wave of AI? In the first wave, artificial intelligence (AI) systems followed clear rules and were directed at individual applications of the algorithms to cover every eventuality. The second wave was the introduction of deep learning and reinforcement learning systems that mapped inputs to outputs to solve a certain type of problem.

The idea of using Artificial Intelligence to understand consumer behavior has been around for a while now. From speculating its accuracy to debating its methods, researchers have always had a keen interest in discussing AI's future in consumer research. Emotion AI is the most noticeable development in this regard. Emotion AI is the sub-set of Artificial Intelligence that tries to understand human expressions, both verbal and non-verbal. Also known as Affective Computing, Emotion AI is the science of recognizing, interpreting, processing, and simulating human expressions. Affective Computing was first coined in 1995 by Rosalind Picard's paper of the same name, published by the MIT Press1.

Tech giants, as well as smaller startups, have been investing in emotion AI for over a decade, using either computer vision or voice analysis to recognize human emotions. Many of these companies started with a focus on market research, analyzing and capturing human emotions in response to a product or TV commercial. Commercial deployments are slowly emerging in virtual personal assistants (VPAs), cars, call centers, robotics and smart devices.