This book presents the fascinating intersection of human cognition and artificial intelligence. Written by leading experts in the fields of cybernetics, cognitive science, and machine learning, this book seeks to bridge the gap between these disciplines and explores the synergies that emerge when humans and machines work together. The book examines the challenges posed by biased data, lack of transparency, and the "black box" nature of some machine learning algorithms. It proposes novel ways to address these issues and foster greater trust and accountability in AI systems. Drawing on cutting-edge research and real-world case studies, it presents a comprehensive and forward-looking perspective on the future of AI and its impact on society. In conclusion, this book offers a compelling exploration of the synergy between human cognition and machine learning, providing insights that are relevant to scholars, researchers, policymakers, and anyone interested in the transformative potential of artificial intelligence.

Highlights the synergy between cybernetics, cognition, and machine learning in the development of intelligent systems Discusses how AI systems augment human capabilities in various fields, such as healthcare, finance, and transportation Explores how human expertise and intuition can guide and improve machine learning

Autorentext

Dr. Vinit Kumar Gunjan is an associate professor in Department of Computer Science & Engineering at CMR Institute of Technology Hyderabad (Affiliated to Jawaharlal Nehru Technological University, Hyderabad). He was awarded the prestigious Early Career Research Award in the year 2016 by Science Engineering Research Board, Department of Science & Technology Government of India. He is a senior member of IEEE, an active volunteer of IEEE Hyderabad section; currently volunteering in the capacity of chairman-IEEE CSS, volunteered in the capacity of Treasurer, Secretary & Chairman of IEEE Young Professionals Affinity Group, IEEE CIS, and IEEE Computer Society. He was involved as organizer in many technical & non-technical workshops, seminars & conferences of IEEE & Springer.

Dr. Sabrina Senatore received her M.S. degree in computer science from the University of Salerno, Italy in 1999 and Ph.D. in computer science from the University of Salerno, in 2004. Currently, she is an associate professor of Computer Science at the University of Salerno, Italy. She is the chair of IEEE CIS Task Force on Intelligent Agents (TFIA) and member of the IEEE CIS Intelligence Society Task Force: Fuzzy Systems for Web Intelligence; she is an associate editor of Information Science, and she is also an editorial board member of the Applied Intelligence Journal and International Journal of Computational Intelligence Theory and Practice. Her current research interests include the development and application of intelligent systems based on the combination of techniques from Soft Computing, Computational Intelligence, Text Mining, Information Retrieval, Semantic Web, and Intelligent Agents, areas in which she has published extensively.

Dr. Amit Kumar is a passionate forensic scientist, entrepreneur, engineer, bioinformatician, and an IEEE volunteer. In 2005 he founded first Private DNA Testing Company BioAxis DNA Research Centre (P) Ltd in Hyderabad, India with an US Collaborator. He has vast experience of training 1000+ Crime investigation officers and helped 750+ Criminal and non-criminal cases to reach justice by offering analytical services in his laboratory. His group also works extensively on Genetic Predisposition risk studies of cancers and has been helping many cancer patients from 2012 to fight and win the battle against cancer. He has driven number of IEEE Conferences, Conference leadership programs, Entrepreneurship development workshops, Innovation, and Internship-related events. Currently He is also a visiting professor at SJB Research Foundation and Vice Chairman of IEEE India Council and IEEE Hyderabad Section.

Inhalt

1. Introduction to Cybernetics, Cognition, and Machine Learning.- 2. Foundations of Cybernetics.- 3. Cognition and Cognitive Systems.- 4. Introduction to Machine Learning.- 5. Cybernetics and Machine Learning Integration.