Table of Contents

Preface

Chapter 1. Levels of Intelligence
What is Intelligence?
Intelligence without neurons: bacteria to plants
How does a nervous system work?
Reflexes: simple behavior
Limitations of reflexes
Connectome
Multiple controllers for muscles
Eye movements: a case study
Many behaviors are social

Chapter 2. Brain and Decision Making
Utility theory
Time and uncertainty
Indecision: Buridan's ass
Limitations of the utility theory
Happiness
Utility theory and the brain
Meaning of action potentials
Evolution of utilities

Chapter 3. Artificial Intelligence
Brain versus computer
Will computers outperform human brains
Synapse vs. transistor
Hardware vs. software
AI on Mars
Is Sojourner still alive?
Autonomous AI
AI and utilities
Robot society and swarm intelligence

Chapter 4. Self-replicating machine
Self-replicating machines
Natural history of self-replicating machines
Multi-talented proteins
Multicellular organisms
Brain evolution
Evolution and Development

Chapter 5. Brain and Genes
Division of labor and delegation
Principal-agent relationship
Brain's incentive

Chapter 6. Why learning?
Diversity of learning
Classical conditioning: a salivating dog
Law of effect and instrumental conditioning: a curious cat
Instrumental meets classical
Instrumental and classical clash
Knowledge: latent learning and place learning

Chapter 7. Brain for Learning
Neurons and learning
Search for the engram
Hippocampus and basal ganglia
Reinforcement learning theory
Pleasure chemical: dopamine
Reinforcement learning and knowledge
Regret and orbitofrontal cortex
Regret neurons

Chapter 8. Social Intelligence and Altruism
Game theory
Death of game theory?
Iterative prisoner's dilemma
Pavlov strategy
Cooperating society
Dark side of altruism
Predicting the behaviors of others
Recursive mind
Social brain
Default cognition: anthropomorphization

Chapter 9. Intelligence and Self
Paradox of self-knowledge
Meta-cognition and meta-selection
Cost of intelligence

Chapter 10. Conclusion: Questions for Artificial Intelligence

About the Author

Daeyeol Lee received his undergraduate degree in economics from Seoul National University in South Korea, and his doctoral degree in neuroscience from the University of Illinois at Urbana-Champaign in the United States. He has held faculty appointments at Wake Forest University, University of Rochester, and Yale University, before joining the Zanvyl Krieger Mind/Brain Institute at the Johns Hopkins University as a Bloomberg Distinguished Professor
in 2019. His research focuses on the brain mechanisms of decision making and high-level cognition.

Reviews

Lee maintains that to understand intelligence it is essential to understand how the brain works, and perforce to become more aware of the recent advances in the field of neuroscience. Furthermore, he has done a great job of discussing, in an extremely readable way, a wide range of important topics shedding light on the nature of intelligence: the difference between animal and human intelligence; the strengths and limitations of artificial intelligence; parallels between the relationship of an employer to its agent and the relationship between genes and the brain; the role of learning in the development of intelligence; and the key role of social intelligence in human life overall. While the text is not light reading, the writing is so accessible that even the careful general reader will gain valuable understanding of what intelligence is and what it does from the perspective of an expert.
*R. Bharath, Emeritus, Northern Michigan University, CHOICE*

This book addresses two fundamental questions
*what it means to be intelligent and why it is important for biological systems to be intelligent. Drawing on key discoveries in neuroscience, computation, psychology, biology, and economics, Lee explains that a flexible ability to deal with the unexpected is central to intelligence and that such a capacity is inextricably linked to the biological imperative for replication and reproduction. There are books about intelligence and books about brains but this is the only one to explain how knowing about the workings of the Venus fly trap, the transistor, RNA, the agency dilemma, and Martian rovers can be useful for understanding either." Matthew Rushworth, FRS, DPhil, Professor of Cognitive Neuroscience, University of Oxford*

In this engaging book, celebrated neuroscientist Daeyeol Lee provides an accessible but authoritative introduction to the core sciences of mind and brain. Building on this, he offers a penetrating and novel argument concerning the differences between biological and artificial intelligence. The book not only contributes key points to one of the most important debates of our time, but also provides an entree into this discussion for both non-experts and experts alike. In this way, Lee helps to create a space for informed and constructive debate concerning the future of our technology, and our relationship with it."
*Matthew Botvinick, MD, PhD, Director of Neuroscience Research, DeepMind and Honorary Professor, Gatsby Computational Neuroscience Unit, University College London*

This ambitious book addresses the complex subject of intelligence. It is an account by a leader on the frontiers of neuroscience and psychology that is crackling with ideas and presented within a new framework of the critical role of intelligence in evolution. The author is engaged in the most up-to-date studies on the broad topic of decision neuroscience. His narrative shows amazing mastery of the essential topics, across a wide range of fields, including psychology, neuroscience, mathematics, probability theory, economic theory, evolution, philosophy, and artificial intelligence. These are all knitted together by a logical sequence of chapters and an engaging narrative style to give new insights into the neural basis of intelligence."
*Gordon M. Shepherd, MD, DPhil, Professor Emeritus in Department of Neuroscience, Yale University School of Medicine*