Springer Emotion and Facial Recognition in Artificial Intelligence: Sustainable Multidisciplinary Perspectives and Applications (Information Systems Engineering and Management, 78)

This book explores one of the most transformative frontiers of modern science the intersection of emotion, facial recognition, and artificial intelligence, in an age where machines are evolving from analytical processors to emotionally perceptive entities. Bringing together leading voices from AI research, psychology, neuroscience, human–computer interaction, and policy, this book delivers an in-depth examination of how intelligent systems are learning to understand, interpret, and simulate human emotions. From theoretical foundations to advanced deep learning models, readers gain a panoramic view of how emotional data can reshape education, health care, mental health diagnostics, business intelligence, governance, and law enforcement. Spanning eighteen comprehensive chapters, the book explores: • Computational models of emotion and facial recognition using cutting-edge AI architectures. • The role of affective computing in sustainable and ethical technology ecosystems. • Applications of emotion AI in mental health, adaptive learning, and personalized education. • Forensic and legal implications of emotion recognition, privacy, and data governance. • The future of emotionally intelligent and human-centric AI systems. Each contribution in this edited book offers a multidisciplinary and globally relevant perspective, blending empirical research with ethical reflection and sustainable design principles. A must-read for academicians, researchers, industry professionals, policy experts, and AI practitioners, this book serves as both a scholarly reference and a visionary roadmap toward emotionally aware and ethically responsible AI. As technology begins to feel, not just think, this book invites readers to explore how the fusion of emotion and intelligence can redefine the future of human–machine coexistence