1st Edition

Foundation, Architecture, and Prototyping of Humanized AI A New Constructivist Approach

By Mark Chang Copyright 2023
    384 Pages 84 Color & 5 B/W Illustrations
    by Chapman & Hall

    384 Pages 84 Color & 5 B/W Illustrations
    by Chapman & Hall

    Humanized AI (HAI), emerging as the next of the AI waves, refers to artificial social beings that are very close to humans in various aspects, beings who are machine-race humans, not digital slaves. Foundation, Architecture, and Prototyping of HAI deploy a novel smalldata approach to vertically explore the spectrum of HAI.

    Different from the popular big-data philosophy that is based on the rigid notion that the connotation of each concept is fixed and the same to everyone, this book treats understanding as a process from simple to complex, and uses the similarity principle to effectively deal with novelties. Combining the efficiency of the Behaviorists’ goal-driven approach and the flexibility of a Constructivists’ approach, both the architecture of HAI and the philosophical discussions arising from it are elaborated upon.

    Advancing a unique approach to the concept of HAI, this book appeals to professors and students of both AI and philosophy, as well as industry professionals looking to stay at the forefront of developments within the field.

    Part 1: Philosophy of Humanized AI in Plain Language

    Chapter 1 The Human-Machine World to Create: Humanized AI

    Chapter 2 The World We Live in and The World in Our Eyes

    Chapter 3 The World in Our Mind: Fundamental Laws and Principles

    Chapter 4 The World to Learn: Cognition and Learning

    Part 2: Humanized AI and Its Approaches

    Chapter 1 A Brief History of AI and Machine-Learning Methods

    Chapter 3 Existing Approaches to Humanized AI

    Chapter 4 New Approach To Humanized AI

    Part 3: Architecture of Humanized AI

    Chapter 1 Three Worlds and Virtual Reality

    Chapter 2 First Designer Stance

    Chapter 3 Dynamic Knowledge Representation

    Chapter 4 Attention Mechanism and Attentive World

    Chapter 5 Learning Mechanism and Knowledge Discovery

    Chapter 6 Adaptive Response Mechanism

    Chapter 7 Effective Teaching

    Part 4: Prototyping Agents - Zda and Lia

    Chapter 1 Functional and Logic Specifications

    Chapter 2 Modularization of Humanized AI Architecture

    Chapter 3 Implementations of Innate Mechanisms

    Chapter 4 Miscellaneous


    Appendix: Tutorial to Common Methods for Narrow AI




    Mark Chang, PhD, is the founder of AGInception and an adjunct professor of Biostatistics at Boston University. He is an elected fellow of the American Statistical Association, a co-founder of the International Society for Biopharmaceutical Statistics. He previously held various positions in pharmaceutical companies, including Scientific Fellow,  executive Director, and Senior Vice President. He is an adaptive design expert and has extensive knowledge in AI for clinical trials. He has published 12 books on artificial intelligence & machine learning, adaptive clinical trial designs, biostatistics, and scientific principles.