Title: AI, Innovation and Global Transformation: Interdisciplinary Perspectives on Technology, Business and Society
Editors: Dr. J. Preetha, and Dr. Siddhartha Mehrotra
ISBN: 978-81-69857-64-2
Chapter: 6
DOI: https://doi.org/10.59646/809/06
Authors: Mrs. G. Abirami, and Mrs. V.G. Anisha Gnana Vincy
Abstract
Artificial General Intelligence (AGI) represents a prospective generation of intelligent systems capable of performing diverse cognitive tasks, transferring knowledge across domains, learning continuously, and adapting to unfamiliar situations. Rather than replacing human intelligence, emerging AGI concepts increasingly emphasize human–AI collaboration, where artificial systems augment human reasoning, creativity, decision-making, and problem-solving. This chapter examines the evolution toward AGI and investigates how human expertise can be integrated with increasingly autonomous AI systems. The study considers foundation models, multimodal intelligence, autonomous agents, continual learning, machine reasoning, human feedback, and collaborative decision-making. A structured methodology is developed to evaluate human–AI collaboration across capability, productivity, accuracy, adaptability, trust, and decision quality. A mathematical framework models collaborative intelligence as a function of AI capability, human expertise, interaction quality, uncertainty, and risk. Synthesized results indicate that appropriately designed human–AI collaboration can outperform isolated human or AI decision-making in several complex tasks. The chapter also examines alignment, explainability, accountability, privacy, bias, autonomy, and governance challenges.
Keywords: Artificial General Intelligence, Human–AI Collaboration, Intelligent Systems, Foundation Models, Autonomous Agents, Collaborative Intelligence