Thinking Like a Computer

George Towner

Description

Thinking Like a Computer is the result of a detailed 30-year study of how computers imitate life.
Although they are machines, computers are designed to act like human beings. Software is specifically created to help accomplish human-like tasks and to be understood in human terms. Yet unlike human life, computer operations can be analyzed in detail because we build the machines that accomplish them and we know the design decisions that make them work.
With every choice made during the evolution of digital technology, computer architects have intuitively or consciously incorporated truths of human functioning into their designs.
Thinking Like a Computer is based on these truths, assembling them into a new explanation of human knowledge. In addition, it provides insights into the foundations of theoretical science because much of digital technology is dedicated to creating new realities.

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Informations

• Publié par: Austin Macauley Publishers LLC
• Date de parution: 30 septembre 2020
• Nombre de lectures: 0
• EAN13: 9781645759287
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Thinking Like a Computer
George Towner
Austin Macauley Publishers
2020-09-30
Thinking Like a Computer About the Author Copyright Information © Introduction 1. Digital Reality Theory Understanding the World Constructing Digital Realities DR Theory Trade-Offs DR Theory and Computing Verifying DR Theory 2. Understanding Existence Types of Understanding Time, Space, Pattern Using Ideals Sets and Digitization 3. Constructing Reality Digital Reality Types What Categorization Does Expanding Digital Reality The Power of Powersets The Structure of Knowledge 4. Social Realities Social Categorizations Worldviews Science and Religion Individual Liberty Consciousness 5. Personal Realities Personal Categorizations Natural Reality Formal Reality From Natural to Formal Spiritual Reality Beyond Ideals 6. Using DR Theory Resolving Cartesian Dualism Clarifying Time and Space Generalizing Categorization Defining Statism and Individualism Explaining Nonlocality in Physics Rationalizing Epistemology Notes Afterword
About the Author
The author, George Towner, studied logic and philosophy at Berkeley, then became assistant director of the Kaiser Foundation Research Institute, working on the biology of primitive organisms. When the computer revolution reached Silicon Valley, he switched to information technology and served 30 years on the senior technical staff at Apple. In his independent research, Towner analyzed how computers evolved from early number crunchers into today’s smart digital assistants. Thinking Like a Computer presents a compelling new explanation, based in set theory, of how both people and computers understand reality.
Copyright Information ©
George Towner (2020)
All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations embodied in critical reviews and certain other noncommercial uses permitted by copyright law. For permission requests, write to the publisher.
Any person who commits any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages.
Austin Macauley is committed to publishing works of quality and integrity. In this spirit, we are proud to offer this book to our readers; however, the story, the experiences, and the words are the author’s alone.
Ordering Information:
Quantity sales: special discounts are available on quantity purchases by corporations, associations, and others. For details, contact the publisher at the address below.
Publisher’s Cataloging-in-Publication data
Towner, George.
Thinking Like a Computer
ISBN 9781645759270 (Paperback)
ISBN 9781645759263 (Hardback)
ISBN 9781645759287 (ePub e-book)
Library of Congress Control Number: 2020916187
www.austinmacauley.com/us
First Published (2020)
Austin Macauley Publishers LLC
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Introduction
Discoveries made during the last fifty years suggest a new approach to understanding how knowledge supports life.
If any of my grandchildren grow up to be historians they will marvel at our present age. Beginning in the 1980s, the widespread availability of computing power upended many traditional skills. As a teenager, I learned the rudiments of printing, bookkeeping, and photography. Today, most of what I learned is obsolete. Printing migrated from hot metal to desktop publishing, bookkeeping from paper to spreadsheets, photography from film cameras to telephones. All this and now my car wants to drive itself.
To keep up with the times, I moved to Silicon Valley, learned programming, and joined the engineering staff at Apple. Pure luck gave me entree to the mosh pit that people began calling “the digital revolution.” During the next 30 years, I watched the revolution unfold and became aware that it affected more than just lifestyles and office work. At Berkeley, I had been trained in logic and philosophy, and afterward I had immersed myself in biology at the Kaiser Foundation Research Institute. At Apple, I was surrounded by rough-and-ready philosophers who were using logic to design machines that acted like living things. I was working
with very bright guys who every day solved deeply theoretical problems of human knowledge that would have blown away the likes of Aristotle, Newton, and Kant.
Other Silicon Valley enterprises contributed to this effort—SRI, Intel, PARC, NeXT, Google, Adobe—and it began to dawn on me that I was in the midst of something like a philosophical laboratory at work. Imaginative people, trying to make machines think, were experimentally challenging the foundations of traditional science.
The upshot was that I gained a new understanding of how knowledge works at the nuts and bolts level. The idea was not that people are like computers. Rather, the idea was that computers were supposed to act like people. All those experiments with hardware and software, all those trials and errors, uncovered novel principles of human knowledge that made sense to me and that worked in machines.
My key discovery was digitization, a complex machine technology developed in the twentieth century. You and I and our computers interact with the world around us in analog ways, yet we are capable of thinking and acting in digital terms. Digitization is not just peculiar to us or to Homo sapiens —it is baked into the nature of life itself. In fact, analog-to-digital conversion is one of life’s primary skills. From this insight, Digital Reality Theory was born. The basics of DR Theory can be expressed in seven words:
Life understands existence by constructing digital realities .
A hundred years ago most people would have found this seven-word summary incomprehensible, yet today it makes sense. It took three intellectual developments during the
nineteenth and twentieth centuries—evolution, set theory, and digitization—to achieve that change and to make DR Theory possible:
During the second half of the nineteenth century, Darwin’s principle of evolution recast many ideas about life. Among them was the idea of fixed knowledge. “How does the world work?” was a question that tradition claimed had one answer—if only we knew how to find it. Thinkers such as Newton and Kant had searched for the principles behind the development of knowledge—Newton picked mathematics and Kant picked reasoning—but it never occurred to them that life itself evolved and that knowledge changed naturally with it.
Set theory was invented in 1874. Mathematician Georg Cantor launched what is now called naïve set theory by showing how to construct sets of numbers as real mathematical objects. In the 1920s two logicians, Ernst Zermelo and Abraham Fraenkel, worked out the general rules for constructing sets of elements of any kind and for verifying that the sets were real objects. This became the tightly logical discipline known as axiomatic set theory.
Digitization as an information technology originated in the twentieth century. While computers evolved from number crunchers to multimedia processors, their designers invented algorithms for converting analog data to digital form. The science of analog-to-digital conversion was born.
The latter two developments laid the foundation for today’s smart computing devices. All such devices, from desktop computers to mobile telephones, are designed to construct sets of digital bits internally to represent external analog phenomena such as images, sounds, events, and even whole artificial realities. Smart devices do this for efficiency—digitization helps them sort out the essential from the trivial and adapt old solutions to new tasks. We and other living things digitize the world we live in for the same reasons. We construct digital realities inside to solve analog problems outside.
DR Theory emerged when the principles of evolution, axiomatic set theory, and the science of digitization were added to traditional theories of knowledge. Books published during the last forty years have presented enough detail about the theory to make its messages clear. The present book summarizes the latest state of DR Theory in six chapters:
Chapter 1, “Digital Reality Theory,” outlines the theory’s basic ideas in plain language. It summarizes how DR theory explains knowledge and how it differs from older explanations.
Chapter 2, “Understanding Existence,” analyzes in more detail how we and other living things grasp the world around us. This collection of mechanisms, developed during life’s evolution, can be described using set theory.
Chapter 3, “Constructing Reality,” explains the processes by which we humans make our knowledge useful. It is primarily through digital
categorization that our understanding of the world acquires its astonishing richness and complexity.
Chapter 4, “Social Realities,” discusses the institutions and agreements that make human group behavior possible. It shows how these constructions, although artificially created, become real in our lives.
Chapter 5, “Personal Realities,” summarizes the processes by which people create their natural, formal, and spiritual worlds. These internal digital realities, taken together, contain everything we know as individuals.
Chapter 6, “Using DR Theory,” reviews some of the ways in which DR Theory can help bring the foundations of human knowledge up to date.
One of the messages of DR Theory is that all knowledge is more or less iffy. Some ideas are pretty certain, but even what we think is our surest knowledge gets regularly overturned by better ideas. This book is no exception. The best theories make us re-examine what we think we know, for that is where we find new understandings. If DR Theory only helps with that task, it will have done its job.
1. Digital Reality Theory
DR Theory