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Emotional AI Integrating Human Feelings in Machine Learning

Arunkumar Thirunagalingam, Pawan Whig

2024Advances in computational intelligence and robotics book series25 citationsDOI

Abstract

In this book chapter, we delve into the evolving field of Emotional AI, exploring how machine learning techniques are being adapted to understand and respond to human emotions. We begin by examining the theoretical foundations of emotional intelligence and its significance in human-computer interaction. Highlighting recent advancements in sentiment analysis, affective computing, and natural language processing, we illustrate how these technologies are enabling machines to interpret and appropriately respond to emotional cues in real-time. Furthermore, we discuss the ethical implications and societal impacts of Emotional AI, addressing concerns such as privacy, bias, and the potential for emotional manipulation. This chapter aims to provide a comprehensive overview of the current state and future directions of Emotional AI, offering insights into its transformative potential across various domains including healthcare, education, and customer service.

Topics & Concepts

Transformative learningFeelingEmotional intelligenceAffective computingField (mathematics)Computer sciencePsychologyArtificial intelligenceCognitive scienceSocial psychologyDevelopmental psychologyMathematicsPure mathematicsAI in Service InteractionsEmotion and Mood RecognitionSentiment Analysis and Opinion Mining
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