Human-Assisted Intelligent Computing

Capture a fresh perspective on AI where human judgment and machine intelligence work together. Human-Assisted Intelligent Computing by Mukhdeep Singh Manshahia, Igor S Litvinchev, Gerhard-Wilhelm Weber, J Joshua Thomas and Pandian Vasa offers a timely, practical exploration of human-in-the-loop systems that reshape decision-making across industries.

This clear, authoritative volume examines methods for integrating human expertise with advanced algorithms—covering interactive learning, hybrid decision-support architectures, explainable AI, and ethical design principles. Richly informed by contemporary research, the text connects theory to real-world applications in healthcare diagnostics, manufacturing automation, finance, and smart-city initiatives, making complex technical concepts accessible to both specialists and interdisciplinary teams.

Readers will gain actionable strategies for designing robust human-assisted intelligent computing solutions: frameworks for collaboration between analysts and models, evaluation metrics for mixed-initiative systems, and guidance on usability, trust, and regulatory considerations. The book is an essential resource for researchers, data scientists, HCI professionals, product managers, and policymakers seeking to deploy responsible, resilient AI systems.

Globally relevant and practical for audiences in North America, Europe, Asia and beyond, this work positions itself at the intersection of human factors and machine intelligence—ideal for university courses, industry practitioners, and research labs pursuing next-generation intelligent systems.

Discover how to harness the complementary strengths of people and machines to build smarter, more trustworthy systems. Order your copy of Human-Assisted Intelligent Computing today and lead the shift toward human-centered AI.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.