Thinking Like a Computer: An Introduction to Digital Reality

By George Towner

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.

• Language: English
• Publisher: Austin Macauley Publishers
• Release date: Sep 30, 2020
• ISBN: 9781645759287

George Towner

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.

Book preview

Thinking Like a Computer

An Introduction to Digital Reality

George Towner

Austin Macauley Publishers

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.

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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 can be outlined in seven words: "Life

understands existence by constructing digital realities."

LIFE UNDERSTANDING EXISTENCE describes a familiar occupation. We do it all the time. Here I use the word understanding in the sense of understanding a language or a game. When I say that I understand French or gin rummy, I’m claiming that in certain situations—such as being asked "ça va?" or being dealt a hand of cards—I know how to respond. I’m only a fraction of life as a whole, and a deck of cards is but a tiny bit of the existing universe, but the same principle scales up.

A branch of philosophy—epistemology, or theory of knowledge—is devoted to explaining how we understand the world (or how we should be understanding it) and judging the results. So DR Theory should be classified as a broad theory of knowledge, because the last three words in its summary—constructing digital realities—describe what we and other living things actually do to understand existence. After reading this chapter you should be able to understand understanding, which sounds like a truly philosophical goal.

DR Theory is based on existing information and explanations. It does not depend on any unpublished experiments or hitherto undiscovered truths. However, it does bring together ideas and trains of thinking that are not usually associated. It assembles a coherent and believable mental picture out of principles that have traditionally been scattered among various scholarly disciplines. Whether that picture is true to life is a matter of judgment in which you are the judge.

The story of DR Theory can be told in ordinary language. Writing it down has not required made-up words or strings of arcane symbols. However, ordinary language is sometimes too broad for DR Theory. For example, one meaning in Webster’s definition of behavior attributes it to inanimate substances ("The behavior of various metals under heat"). DR Theory restricts behavior to living things. I have tried to flag instances where DR Theory uses ordinary words in limited ways so this book can stick with plain language—a small price to pay for avoiding jargon and scholarly ratiocination.

Understanding the World

For starters, I’m going to try to define exactly what the subject of DR Theory—life understanding existence—covers.

Life includes all living things on planet Earth, from bacteria to rock stars, plus their footprints—all the artifacts and environmental changes they make. It also includes some semi-independent parts of living bodies (such as chloroplasts and mitochondria) and many groups of living things (such as species and societies). I mean by life every object or assembly in physical existence that manifests or is a consequence of the phenomenon of being alive.

For example, an individual beaver is a part of life, but so is the genus Castor and so are the dams and lodges that beavers build. During its lifetime, each individual beaver constructs a digital reality within itself to help it build dams across one or more particular streams. Castor, the beaver genus, constructs a more general digital reality to help all beavers cope with all streams. The individual beaver stores its digital reality in its nervous system; Castor stores and transmits its reality in the beaver genome. Long ago the class Mammalia added to that genome a digital reality of urges and signals that helps Castor and other large animals reproduce; and so on. If you are a beaver, successfully behaving like one depends on having