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How to Grow a Robot: Developing Human-Friendly, Social AI (The MIT Press)

✍ Scribed by Mark H. Lee


Publisher
MIT Press
Year
2020
Tongue
English
Leaves
385
Edition
Illustrated
Category
Library

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✦ Synopsis


How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed. Most robots are not very friendly. They vacuum the rug, mow the lawn, dispose of bombs, even perform surgery-but they aren't good conversationalists. It's difficult to make eye contact. If the future promises more human-robot collaboration in both work and play, wouldn't it be better if the robots were less mechanical and more social? In How to Grow a Robot, Mark Lee explores how robots can be more human-like, friendly, and engaging. Developments in artificial intelligence-notably Deep Learning-are widely seen as the foundation on which our robot future will be built. These advances have already brought us self-driving cars and chess match-winning algorithms. But, Lee writes, we need robots that are perceptive, animated, and responsive-more like humans and less like computers, more social than machine-like, and more playful and less programmed. The way to achieve this, he argues, is to "grow" a robot so that it learns from experience-just as infants do. After describing "what's wrong with artificial intelligence" (one key shortcoming: it's not embodied), Lee presents a different approach to building human-like robots: developmental robotics, inspired by developmental psychology and its accounts of early infant behavior. He describes his own experiments with the iCub humanoid robot and its development from newborn helplessness to ability levels equal to a nine-month-old, explaining how the iCub learns from its own experiences. AI robots are designed to know humans as objects; developmental robots will learn empathy. Developmental robots, with an internal model of "self," will be better interactive partners with humans. That is the kind of future technology we should work toward.

✦ Table of Contents


Contents
Preface
Acknowledgments
I. What's Wrong with Artificial Intelligence?
1. The Nature of the Problem
Acting and Thinking
The Social Robot
The Role of Artificial Intelligence
Intelligence in General
Brains Need Bodies
The Structure and Theme of This Book
Coping with the Pace of Change
A Note on Jargon
2. Commercial Robots
Domestic Robots and Service Robots
Field Robotics
Robotic Road Vehicles
Medical Robots
Swarm Robotics
Entertainment Robots
Companion Robots
Humanlike Robots?
Observations
3. From Research Bench to Market
Bin Picking
Biorobotics
Care and Assistive Robots
Affective Computing
Humanoid Robots
Why Has Industrial Robotics Been So Successful?
The Current State of Robotics
Observations
4. A Tale of Brute Force
Searching through the Options
The World Chess Champion Is a Computer—So What?
Computer "Thinking''
The Outcome
Observations
5. Knowledge versus Power
How Can Knowledge Be Stored for Utilization?
Common Sense Knowledge
Search Is a Standard Technique
Symbols and Numbers
Learning to Improve
Feature Engineering
Observations
6. A Little Vision and a Major Breakthrough
The End of Feature Engineering
What Happened?
Observations
7. The Rise of the Learning Machines
The Evolution of Machine Learning
Data Mining in Supermarkets
Learning Algorithms That Learn Algorithms
Discovering Patterns
Big Data
Statistics Is Important, but Misunderstood
The Revolution Continues—with Deep Zero
Observations
8. Deep Thought and Other Oracles
AI Is a Highly Focused Business
Task-Based AI
Machine Oracles
Knowledge Engineering
Social Conversation
Observations
9. Building Giant Brains
Brain-Building Projects
Whole Brain Emulation (WBE)
The Brain Is a Machine—So What?
Basic Artificial Neural Networks (ANNs)
Different Approaches: AI and Brain Science
More Advanced Networks
Predictive Coding and Autoencoders
Issues with ANNs
Simulation Problems for Robots
Observations
10. Bolting It All Together
The Complexity of Modular Interactions
How Can Computers Represent What They Know and Experience?
The Limitations of Task-Based AI
General AI
Master Algorithms
Biological Comparisons
Superintelligence (SI)
Integrating Deep Artificial NeuralNetworks (ANNs)
Observations for Part I
II. Robots That Grow and Develop
11. Groundwork—Synthesis, Grounding, and Authenticity
The Classical Cybernetics Movement
Modern Cybernetics
Symbol Grounding
The New Robotics
Observations
12. The Developmental Approach—Grow Your Own Robot
The Role of Ontogeny: Growing Robots
Sequences, Stages, and Timelines
Constraints on Development
Start Small and Start Early
The Importance of Anatomy
The Amazing Complexity of the Human Body
Autonomy and Motivation
Play—Exploration and Discovery without Goals
An Architecture for Growth
Observations
13. Developmental Growth in the iCub Humanoid Robot
iCub—A Humanoid Robot for Research
Managing the Constraints of Immaturity
Vision, Gazing, and Fixations
Motor and Visual Spaces
Object Perception
Experiment 1—Longitudinal Development
Experiment 2—The Generation of Play Behavior
How Does It Work?
III. Where Do We Go from Here?
14. How Developmental Robots Will Develop
How Developmental Robots Behave
Taught, not Programmed
Knowing Oneself and Other Agents
Self-Awareness Is Common in Animals
Robot Selves
Consciousness
Communication
Developmental Characteristics
Will All This Happen?
We Must Get Out More . . .
Observations
15. How AI and AI-Robots Are Developing
Task-Based AI
Human-Level AI (HLAI)
Deep AI
Robot Developments
Social Robots
Artificial Human Intelligence (AHI)
Observations
16. Understanding Future Technology
Rapid Growth—It's Not Really Exponential
Growth Patterns in the Twenty-First Century—So Far
Artificial General Intelligence (AGI)
Deep Networks, Learning, and Autonomous Learning
Are There Any Dead Certainties?
Trust, Validation, and Safety
The Product-Centered Viewpoint
The Crucial Role of Humans
The Ethical Viewpoint
Lessons from Opaque and Unregulated Markets
Observations
17. Futurology and Science Fiction
Are We Smart Enough to Know How SmartAnimals Are?
What Kind of World Do We Live In?
Futurology, Expert Opinion, and Meta-opinions
Threats on the Horizon?
Superintelligence and the Singularity
Transhumanism—Downloading the Brain
Imminent Threats
Toward Dystopia?
It's Not All Doom and Gloom!
Threats in Perspective
Final Remarks
Appendix: A Principles for the Developmental Approach
Notes
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 15
Chapter 16
Chapter 17
Bibliography
Index


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