Emotional Artificial Intelligence

Practical Challenges and Applications

Rajesh Kumar Dhanaraj, S. Aanjankumar, Malathy Sathyamoorthy, S. Poonkuntran, Monoj Kumar Muchahari

• Publisher: Academic Press
• Year: 2026
• Topic: Psychology
• eBook ISBN:
  9780443447457
• Subtopic: Neuroscience
• Index: Psychology

Emotional Artificial Intelligence: Practical Challenges and Applications explores the intersection of artificial intelligence and human emotions, challenging the myth that AI will replace humans. Instead, it emphasizes how emotional AI can enhance collaboration, improving efficiency across fields like healthcare, transportation, and space exploration. The book explores foundational theories such as Goleman's emotional model and Ekman's emotion theory, discussing methodologies for understanding human emotions through natural language processing and the ethical implications of AI in decision-making. It showcases real-world applications, from virtual nurses to emotion-aware driving systems, illustrating how these technologies can improve daily interactions and outcomes.This essential resource equips researchers, practitioners, and policymakers with practical insights for integrating emotional AI into diverse domains. By addressing the complexities of human emotion recognition and ethical frameworks, it provides a forward-looking perspective on enhancing collaboration between humans and AI, ultimately driving improved productivity and efficiency. - Provides a thorough examination of emotional AI, integrating foundational theories and methodologies to help readers understand human emotions in the context of artificial intelligence - Showcases practical applications of emotional AI across various fields, including healthcare and transportation, demonstrating how these technologies improve daily interactions and outcomes - Addresses the ethical implications of deploying emotional AI - Offers a forward-looking perspective on emerging trends, equipping readers with insights to navigate the evolving landscape of human-centered artificial intelligence

Table of contents

• Title of Book
• Chapter 1 Explainable AI in emotional artificial intelligence: Challenges and applications
• Chapter 2 Advancing emotional intelligence in artificial intelligence: Challenges and applications
• Chapter 3 Recent advancements and techniques in NLP and emotion-based decision making in AI
• Chapter 4 Building models for emotional AI: A case study on sentiment analysis using python
• Chapter 5 Fully automated vs. semi-automated transportation system: A comparative study on graph neural network
• Chapter 6 Why tend not to adopt? Adoption resistance of chatbots in tourism and hospitality in India
• Chapter 7 Accountability in emotional AI: Legal responsibilities and implications of misinterpreted emotions
• Chapter 8 Unleashing the potential of AI with human doctors: Role of patient diagnosis with ensemble models
• Chapter 9 GANs beyond Earth: The GAN revolution for imaging, segmentation and human space exploration
• Chapter 10 Translating neural activity into language: A machine learning approach for EEG-based thought-to-text conversion
• Chapter 11 Empowering clinical diagnosis with emotionally intelligent AI: A deep ensemble framework for skin cancer detection
• Chapter 12 Emotion-based decision-making in Artificial Intelligence: New developments and trends in Natural Language Processing
• Chapter 13 Case study on gesture-based emotion AI in blood pressure detection: Revolution in healthcare sectors
• Chapter 14 Ethical and legal standards, policies and regulations in emotional AI: Myths and realities
• Chapter 15 Emotional AI tutors a case study on adaptive teaching using facial expression recognition
• Chapter 16 Exporing emotions and sentiment analysis in AI: An evolutionary algorithm based perspectivel
• Chapter 17 Case study on emotion-aware driver assistance systems in Tesla car
• Index