Document Text Content
How Alan Turing invented the computer, helped win World War
II and left us with one of the greatest puzzles of our time: are humans
simply computers or are we more than that? Many scientists think we
have a tenuous hold on the title, “most intelligent being on the planet”.
They think it’s just a matter of time before computers become smarter
than us, and then what? This book charts a journey through the science
of information, from the origins of language and logic, to the frontiers of
modern physics. From Lewis Carroll’s logic puzzles, through Alan Turing
and his work on Enigma and the imitation game, to John Bell’s inequality,
and finally the Conway-Kochen ‘Free Will’ Theorem. How do the laws
of physics give us our creativity, our rich experience of communication
and, especially, our free will?
Can a computer win the imitation game and pass the Turing Test?
Why do creative people make better mates than rich people?
Why are humans bad at mathematics, yet so creative?
Could an infinite number of monkeys write Hamlet?
Is our brain a quantum computer?
Is free will an illusion?
James Tagg is an inventor and entrepreneur. A pioneer of
touchscreen technology, he has founded several companies, including
Truphone, the world’s first global mobile network. He holds numerous
patents, filed in over a hundred countries. He studied Physics and
Computer Science at Manchester University, Design at Lancaster
University and Engineering at Cambridge University. He lives with his
family on a farm in Kent, England.
www.jamestagg.com
“I can’t tell you when the last time was that I had this much fun
reading and using my brain. From the very beginning, James Tagg had
me hooked with the premise; the question of whether or not humans are
the most intelligent beings on the planet....”
Janet, Netgalley
“This is a fantastic book. It seams together cutting edge
neuroscience, psychology, thought experiments, artificial intelligence/
machine learning, mathematics and even some history!...”
PFJ H., Amazon
“Hard work to read, but makes you think about the nature of human
intelligence and AI...”
Brian Clegg, Popular Science
“This is a fat book that covers a huge amount of ground. James’
topic is primarily the brain and how we think, but there is a running
theme contrasting the human brain with computers. His thesis is that
computers can never think like humans (for example, that they can never
be truly creative) and he explores many fields from philosophy and logic
to mathematics in pursuit of this proof....”
R. Hanbury, Amazon
If you have enjoyed reading this book please leave a review and if
you would like to hear more, or come to one of my talks, please join the
mailing list at: www.jamestagg.com/updates.
Are the Androids
Dreaming Yet?
Amazing Brain.
Human
Communication,
Creativity &
Free Will.
Are the Androids
Dreaming Yet?
Amazing Brain.
Human
Communication,
Creativity &
Free Will.
JAMES TAGG
Hurst Farm Books
An Imprint of
Hurst Farm Enterprises
Published by Hurst Farm Books
Hurst Farm, Dairy Lane, Crockham Hill, TN8 6RA.
+44 1732 807246
12 Williams Road, Chatham, NJ 07928
+1 646 355 1250
www.jamestagg.com
bookinfo@jamestagg.com
Copyright © James Tagg 2015
The Moral Right of the author has been asserted.
All rights reserved. Without limitation to copyright, no part of this publication may be
reproduced, stored, or transmitted in any form without the prior written permission of
the copyright owner and the publisher.
A catalogue record for this book is available from the British Library.
Publisher’s Cataloging-in-Publication Data
Tagg, James, 1964-
Are the Androids Dreaming Yet?: Amazing Brain.
Human Communication, Creativity & Free Will. /
James Tagg.
pages cm
Includes bibliographical reference and index
ISBN: 978-1-910464-03-8 (softcover)
ISBN: 978-1-910464-01-4 (ebook)
1. Creative ability. 2. Communication—Social aspects.
3. Technology—Social aspects. 4. Mind and body. 5.
Computers and civilization. I. Title.
T174 .T24 2015
303.48`34—dc23
Library of Congress Control Number: 2014945686
(hardback)
p2 220415 postc
To my family,
who have patiently listened to my interminable
ramblings about ‘Elephantine’ Equations.
PREFACE
ACPMM, Wolfson College, Cambridge
“A man may have twenty years
of experience, or one year of
experience twenty times.”
Mike Sharman
“Rules are for the obedience of
fools and the guidance of wise
men.”
Douglas Bader
I
am an inventor. I’ve always been an inventor. Ever since childhood
I’ve tinkered with electronics and computers, taking things apart
and putting them back together. There is no academic course
for inventing, so I had to choose my own path through school and
University. I studied design, physics and mathematics at secondary
school, and engineering and management at University. Part of that time
was spent in the Engineering Department of Cambridge University on a
particularly special course.
x
Are the Androids Dreaming Yet?
Mathematical Bridge, Cambridge
Every autumn about thirty graduate students arrive at the
Engineering Department in Cambridge to join the Advanced Course in
Design, Manufacturing and Management. They expect to spend the year
walking among the city’s hallowed spires, attending lectures, bumping
into Stephen Hawking and punting on the River Cam.
Instead, they get quite a shock!
In 1989, I joined the course. There were twenty-six engineers, a
psychologist and a physicist – me. There was no prescribed syllabus;
instead the course used learning-by-experience and lectures from the
experts in a given field. To study advertising, you might visit a top London
agency, for shipbuilding a shipyard on the Clyde. If you were unlucky
enough to find these two lectures scheduled for the same week, you had
to travel the length of Britain. The course runs a half dozen minibuses
to solve this transport problem. Every four weeks we would undertake a
project in a different company. I remember designing pit props for coal
mines and imaging software for a weaving company. At the end of each
project we presented our findings to each other and, with eight projects
and thirty students, this made for a great many presentations. To keep
the process manageable, the course put great store in teaching us the art
of communication.
These days I design large complex systems, and clear communication
is extremely important. My ideas are often turned into working products
and, if those products have flaws, a post-mortem usually shows the cause
Preface
xi
was a breakdown in communication. Of course, this may be a purely
personal failing, but when I talk to people in other companies they
report the same problem. It seems we all find communication difficult.
have wondered for many years why it is called the ‘art of
communication’. Surely it’s a science, governed by bits, bytes and
bandwidth. That might be true of the symbols in an email – they are
clearly encoded symbolically – but is the understanding in our brains
simply encoded by symbols? What is the physics that underlies human
understanding?
Each summer I go on holiday to escape engineering for a couple of
weeks. While away I indulge my passion for reading books by the likes
of Douglas Hofstadter, David Deutsch and Stephen Hawking. One book
that struck me years ago was Roger Penrose’s The Emperor’s New Mind.
In it, he tackles the question of what happens in the human brain when
we understand something. He extends an idea put forward by J.R. Lucas
of Oxford University that minds must be more powerful than computers
because they do something computers cannot: namely to step beyond
mere rules and see truth. Colloquially we call this ‘common sense’ or
‘stepping outside the box’.
The Lucas argument uses the theories of Gödel and Turing to
show computer algorithms have limitations. Some things are simply
not computable. Computers can do many useful things, but they cannot
discover new mathematical theorems, such as a proof of Fermat’s Last
Theorem. In 1996, Andrew Wiles succeeded in finding a solution to this
problem. This presents a paradox, solved only if we conclude Andrew
Wiles is not a computer. Indeed, since most mathematicians discover at
least one theorem during their lives, we must conclude no mathematician
is a computer! This is controversial. Most philosophers tend to the
view put forward by Daniel Dennett that the Universe is an entirely
determined place and any personal sense of free will and creativity is
an illusion. In Dennett’s worldview, Andrew Wiles is a special purpose
machine that was always destined to solve Fermat’s Last Theorem. I
believe this model is flawed. It is my aim in this book to show you why.
Indeed I am going to go further and argue all human creativity is noncomputational;
art, communication, understanding – all are based on
non-algorithmic principles.
If you consider creative thinking deeply enough you’re inevitably
drawn into the question of whether we have free will. When I get to
work each morning, the first thing I do – after a cup of coffee, obviously
– is choose which creative task to tackle first. I feel this choice is freely
made, but the determined determinists assure me I am wrong and my
xii
Are the Androids Dreaming Yet?
decision was already made. As Daniel Dennett says, “You have no free
will. Get over it!” They say I am effectively an avatar in some giant cosmic
computer game, going about my business in an entirely predefined way. I
do not agree! If they are right all the coincidences and chance actions of
my life were fixed at the time of the Big Bang. I feel this must be wrong,
but finding a chink in the determinist armor is hard work; the laws of
physics as we know them today are almost exclusively deterministic.
This book lays out the options – the chinks – that would allow free will
to enter our Universe.
To understand human thinking we would really like to look inside
a working human brain. We can’t do this yet. All we can do is observe
minds at work when they communicate with one another. If our minds
think non-computationally – as I believe – we should be able to see them
struggle when they have to translate thoughts into symbolic form. The
more symbolic, the harder it will be. This is indeed what we observe: faceto-face
communication is easy, while formal written modes are much
harder. We will explore the difference between human and computer
communication as our first step in locating the weakness in the armor
of determinism.
What do I Believe?
As a scientist, I ought not to have beliefs. I should have theories and
working assumptions. But, as a human being, I must admit believing
certain things are true. Science does not forbid beliefs. It just requires
you to be prepared to have one overturned if a better one comes along.
Richard Feynman summed this up in a lecture he delivered at Cal Tech:
“If you want to discover a theorem,” he said, “first, you guess, then you
work out some effect predicted by the theorem. Finally, you see if the
effect happens in the real world. If it does, you have a good theory. If the
effect happens a little differently, you will need to look for a better theory.”
Here are some of my overturn-able beliefs.
Preface
xiii
Beliefs
• We have true free will. We consciously decide our actions and
these decisions are in no way predetermined. We shape the
future. Allowing for free will is, therefore, a boundary condition
for any theory of our Universe.
• The world is an amazing place, but understandable. We can
understand the Universe through the application of thought and
reason.
• There is only one Universe and it appears to make sense.
• Humans think creatively, computers do not.
• The process of understanding and communication is complex,
much more complex than the digital theorems of Claude
Shannon and Harry Nyquist.
• Understanding is hard.
• The communication of understanding is even harder.
CONTENTS
Preface
ix
Introduction – Experiments, Multimedia and Puzzles 1
Chapter 1 – Mind Over Computer 3
Deep Blue 5
Man v Machine 11
Intelligence 25
The Learning Brain 35
Determinism 41
Creative Theories 49
Chapter 2 – Understanding 53
Bad Understanding Can Kill 59
The Imitation Game 65
Chapter 3 – Body Language & Banter 77
Chapter 4 – The Brain 95
Thinking 117
Chapter 5 – Knowledge 127
Chapter 6 – Kittens & Gorillas 147
Chapter 7 – Complexity & Chaos 161
Chaos 171
Chapter 8 – ∞ 177
Chapter 9 – Known Unknowns 191
The Game of Math 199
Chapter 10 – Turing’s Machine 209
The Machine 221
Chapter 11 – Software 229
Silver Bullets Can’t be Fired 233
Consequences 257
Chapter 12 – Hyper-Computing 273
Chapter 13 – Hyper-Communication 285
Chapter 14 – Creativity 295
Chapter 15 – Free Will 313
Schrödinger’s Cat 325
Twins 331
Does God have Free Will? 339
The Free Will Theorem 343
Free Will Universe 351
Chapter 16 – The Quest for Knowledge 355
Awards for Discovery 365
Chapter 17 – The Future 371
Appendix 1 – Acknowledgments 374
Appendix 2 – Bibliography 382
Appendix 3 – Puzzles and Experiments 395
Appendix 4 – Conventions in the Book 397
Appendix 5 – Index of Theorems 401
Index 405
“It is no good getting furious if
you get stuck. What I do is keep
thinking about the problem
but work on something else.
Sometimes it is years before I see
the way forward. In the case of
information loss and black holes,
it was 29 years.”
Stephen Hawking
Introduction
EXPERIMENTS,
MULTIMEDIA AND
PUZZLES
Throughout this book you will come across experiments to try,
multimedia references to track down, and puzzles to solve.
You can get additional information at www.jamestagg.com/
understanding.
If you undertake an experiment I would appreciate your leaving a
note of your results on the website and making useful comments on the
blog.
Most of the experiments and puzzles are quick and simple. The
puzzles I have set often benefit from creative thinking. I have made
finding the answers to these problems a little hard, so you are not
tempted to cheat. I want you to try to solve the problems and ‘feel’ your
brain working.
This book argues that intuitive thought solves problems in a
different way to analytical thought. The process takes time and often
benefits from putting a problem to one side while you use your mind
to process foreground tasks. I hope you read this book at a time when
the website is not available – or at least don’t peek. Give your intuitive
thought processes time to work.
Graham Wallas described the process of creative thinking in 1926
and I think it is still one of the best models we have:
First you must prepare and become fully acquainted
with the problem. It might seem impossible but don’t despair,
just commit to it. Next, you should leave the problem to
stew – incubation, he called it. After a while, you will feel
a solution is at hand. You don’t quite have it yet but you are
2 Are the Androids Dreaming Yet?
sure you will. This is intimation. Finally, some inspiration or
insight will pop into your head – this is the Eureka moment.
Now you have a solution but intuitive thinking is far from
infallible. You will need to check the solution and may find
your answer wrong the first few times. Persevere; you will
get there in the end.
As a warm-up exercise, let me give you a simple childhood riddle
to solve.
A man lives on the twentieth floor of a skyscraper with an
old elevator. Each morning he gets into the elevator and
goes down to the ground floor, but each evening he gets
into the elevator, travels up to the tenth floor, gets out, and
walks the rest of the way. Why?
ANSWER IN YOUR OWN TIME
ddd
Chapter 1
MIND OVER
COMPUTER
Computer versus Human
“I visualize a time when we will
be to robots what dogs are to
humans, and I’m rooting for the
machines.”
Claude Shannon
“The question of whether
computers can think is just
like the question of whether
submarines can swim.”
Edgar Dijkstra
“The Three Laws of Robotics:
1. A robot may not injure a
human being or, through
inaction, allow a human
being to come to harm;
2. A robot must obey the orders
given it by humanbeings
except where such orders
would conflict with the First
Law;
3. A robot must protect its own
existence as long as such
protection does not conflict
with the First or Second Law.
The Zeroth Law: A robot may
not harm humanity, or, by
inaction, allow humanity to
come to harm.”
Isaac Asimov, I, Robot
Kasparov versus Deep Blue
Deep Blue
It is 1997 and we are on the 39th story of the Equitable Center in New
York, watching a chess match. It’s no ordinary match. Two men sit
opposite each other. One, a neatly suited figure, stares intently at the
board. You can almost see the heat rising from his head as he processes
the possibilities before him. The other, sits implacably calm and, before
each turn, looks to a screen at the side of the board, reads the instruction,
and makes his move.
This is the famous match between Garry Kasparov and IBM’s Deep
Blue. Kasparov, a child prodigy, became world chess champion at the age
of fifteen and, to this day, holds the record for the highest chess ranking
ever achieved. Some consider him one of the most intelligent people on
the planet. His opponent, Deep Blue, is a massively parallel chess-playing
computer built by IBM’s Watson Research Laboratory. The machine itself
sits a few blocks north of the tournament in an air-conditioned room,
and relays the moves over a phone line to Joe Hoane, the IBM researcher
who moves the pieces.
Six months earlier, in Philadelphia, Kasparov won against Deep Blue.
This is the rematch and has generated a worldwide media frenzy. Tickets
to the event are sold out and most news organizations give a blow-byblow
report each day. On the eighth day of the tournament Kasparov and
Deep Blue are level pegging. Kasparov is playing an opening he knows
well. It’s one designed to be hard for computers to play and has been
tested extensively against Fritz, a chess computer Grand Masters use for
practice. But Deep Blue doesn’t seem fazed. Kasparov is visibly tired. On
the 16 th move he makes a dreadful blunder and sinks into despair. An
hour later, after some moments of quiet contemplation, he tips over his
6 Are the Androids Dreaming Yet?
king, gets up, and leaves the room. Kasparov has resigned, Deep Blue has
beaten him 3½ to 2½ points and is now the most powerful chess player
on the planet.
Later, when interviewed about his experience, Kasparov thought
Deep Blue must have been assisted by humans during the games because
the program appeared to play intuitively. The rules of the tournament
allowed humans to work on the program between matches, but not
during actual play. The argument has never been settled, and Deep
Blue was long ago dismantled. These days chess players avoid big public
matches against computers, arguing it is really a different sort of game.
A computer’s ability to crunch mathematically through all the many
possibilities means a chess player must play without error against a
machine, but can play a more interesting and fluid match against a fellow
human.
Chess is computer-friendly because it is a finite problem. You always
win, lose or draw. The game can’t go on forever because any position that
repeats itself more than three times is declared a draw, and if a player
makes 50 moves without moving a pawn or taking a piece, the game
is also declared a draw. In a typical game, each player makes 40 moves,
and on each turn you can choose from 30 possible moves. Although this
equates to a huge number of options, it is still a finite number.
It is possible, therefore, to create a perfect chess-playing machine.
Such a machine would project any position it encountered through
every permutation to the endgame. But, although chess is solvable using
brute force this might not be practical in our Universe. The storage
required to hold all the possible positions being analyzed would be
vast – needing most of the atoms in the Universe. You would need to
pack this information into a small enough space to allow fast retrieval in
order to play the first 40 moves in two hours. This would require storing
all the information within a sphere no larger than three light minutes.
Putting that much data in such a small space would exceed the Hawking
Bekenstein bound – a limit on the information carrying capacity of
space-time put forward by Stephen Hawking and Jacob Bekenstein
– causing the region of space-time to collapse to a black hole! Despite
these minor technical problems, an ingenious algorithm could be made
that was unbeatable: chess is essentially computable.
The term algorithm will often arise in the book, so it is worth giving
a little history. The word comes from the name of an 8 th Century Persian
mathematician, Al-Khwarizmi, and means a step-by-step procedure. We
use one whenever we do long division or look up a phone number on
Mind over Computer
7
The Music of Emily Howell
our mobile phone. It is any mechanical procedure you perform without
thinking about it. Computers are always executing an algorithm; that’s
what they do.
Fast forward to 2010 and Centaur Records releases a new classical
music CD featuring the piano music of Emily Howell. Critics are
enthusiastic about the new talent. She has composed music in a broad
range of classical and contemporary styles. You can find some examples
on my website.
But, it transpires, Emily is a computer, the brainchild of David
Cope from the University of Santa Cruz. On hearing this news critics
revise their opinion of the compositions – “repetitive and formulaic,”
“not real music,” “pastiche”. Listen again to the music and see whether
you have changed your opinion. Whatever you think, Emily has made
a good attempt at composing in the style of several great composers: J.S.
Bach and Franz Liszt, as well as modern ones such as Stockhausen and
8 Are the Androids Dreaming Yet?
Philip Glass. The compositions would get a reasonable technical score in
an exam, better than many of my attempts, but are these compositions
truly art?
There’s no question computers are gaining ground on us in certain
mathematically oriented tasks – playing chess, musical composition, and
various modeling tasks. But attempts to have them work with words and
ideas have generally produced dismal results. Until now.
In 2008, IBM unveiled Watson: a computer capable of answering
general knowledge questions. Watson has an enormous database of
human knowledge: the Encyclopedia Britannica, a billion web pages,
the entire text of Wikipedia and millions of books. It uses artificial
intelligence to trawl through this vast reservoir of knowledge and answer
questions using a statistical approach. In 2011, Watson featured as a
contestant on Jeopardy, the American quiz show, where it beat the two
record-holding contestants – the one with the highest number of wins
and the one with most consecutive wins. Let me give you a few sample
questions and see how you fare.
Question 1.
Question 2.
Question 3.
It can mean to develop
gradually in the mind or to
carry during pregnancy.
William Wilkinson’s “An
Account of the Principalities
of Wallachia and Moldavia”
inspired this author’s most
famous Novel.
Its largest airport is named
for a World War II hero; its
second largest, for a World
War II battle.
Watson answered questions one and two correctly but failed on
question three. You can probably see the final question is posed in poorly
structured English and this threw off Watson’s comprehension algorithm.
Mind over Computer
9
IBM’s Watson Plays Jeopardy
Ignoring the odd hiccup, Watson is much better at Jeopardy than a
human. Should humans be worried? First chess, then music, now general
knowledge, will all human endeavors succumb to a computer? What will
be our purpose on the planet if this happens?