1985
ENGINES OF CREATION
by K. Eric Drexler
foreword by Marvin Minsky
(C) Copyright 1986, K. Eric Drexler
Used with permission of K. Eric Drexler
Electronically Enhanced Text (c) Copyright 1996, World Library(R)
AUTHOR'S INTRODUCTION TO THE ELECTRONIC EDITION OF
ENGINES OF CREATION
-
I'm pleased that World Library, Inc. has chosen to include Engines
of Creation in their Library of the Future Series Second Edition.
Engines of Creation is the first book on the subject of
nanotechnology, that is, thorough control of the structure of matter
at the molecular level. One result of this anticipated capability is
molecular manufacturing, which will enable products to be made
cheaply, cleanly and reliably. We can expect far-reaching consequences
for medicine, the economy, the military, and the environment.
I completed Engines of Creation in 1985, and there has been much
progress in this new field since then. We have passed several
milestones (for example, successful engineering of devices made of
protein), and undertaken research projects (the Aono Atomcraft Project
in Japan, for example). The respected scientific journal Nature (7 Feb
1991) has stated "Nanotechnology seems destined to become Japan's next
priority target for industrial research." Together with new
proposals for implementation, these facts paint a picture of major
developments just around the corner rather than in the indefinite
future.
Engines of Creation suggests ways to reduce problems resulting
from the new technologies. One of these ways is through the
development of Hypertext publishing services. These services will
store much of the world's knowledge electronically, easily accessed
on-line. New ideas will constantly be introduced and debated while
being efficiently compared to previously known concepts.
The Library of the Future Series is a major step towards gathering
much of the world's knowledge in an electronic format. Its ability
to search and retrieve topics or ideas for reference and study heralds
a new era.
The Afterword of this book tells readers how to get updated
information on the progress of nanotechnology.
-
K. Eric Drexler
May 1991
FOREWORD
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K. ERIC DREXLER'S Engines of Creation is an enormously original book
about the consequences of new technologies. It is ambitious and
imaginative and, best of all, the thinking is technically sound.
But how can anyone predict where science and technology will take
us? Although many scientists and technologists have tried to do
this, isn't it curious that the most successful attempts were those of
science fiction writers like Jules Verne and H. G. Wells, Frederik
Pohl, Robert Heinlein, Isaac Asimov, and Arthur C. Clarke? Granted,
some of those writers knew a great deal about the science of their
times. But perhaps the strongest source of their success was that they
were equally concerned with the pressures and choices they imagined
emerging from their societies. For, as Clarke himself has
emphasized, it is virtually impossible to predict the details of
future technologies for more than perhaps half a century ahead. For
one thing, it is virtually impossible to predict in detail which
alternatives will become technically feasible over any longer interval
of time. Why? Simply because if one could see ahead that clearly,
one could probably accomplish those things in much less time- given
the will to do so. A second problem is that it is equally hard to
guess the character of the social changes likely to intervene. Given
such uncertainty, looking ahead is like building a very tall and
slender tower of reasoning. And we all know that such constructions
are untrustworthy.
How could one build a sounder case? First, the foundations must be
very firm- and Drexler has built on the soundest areas of
present-day technical knowledge. Next, one must support each important
conclusion step in several different ways, before one starts the next.
This is because no single reason can be robust enough to stand
before so many unknowns. Accordingly, Drexler gives us multiple
supports for each important argument. Finally, it is never entirely
safe to trust one's own judgments in such matters, since all of us
have wishes and fears which bias how we think- without our knowing it.
But, unlike most iconoclasts, Drexler has for many years
courageously and openly exposed these ideas to both the most
conservative skeptics and the most wishful-thinking dreamers among
serious scientific communities like the one around MIT. He has
always listened carefully to what the others said, and sometimes
changed his views accordingly.
Engines of Creation begins with the insight that what we can do
depends on what we can build. This leads to a careful analysis of
possible ways to stack atoms. Then Drexler asks, "What could we
build with those atom-stacking mechanisms?" For one thing, we could
manufacture assembly machines much smaller even than living cells, and
make materials stronger and lighter than any available today. Hence,
better spacecraft. Hence, tiny devices that can travel along
capillaries to enter and repair living cells. Hence, the ability to
heal disease, reverse the ravages of age, or make our bodies
speedier or stronger than before. And we could make machines down to
the size of viruses, machines that would work at speeds which none
of us can yet appreciate. And then, once we learned how to do it, we
would have the option of assembling these myriads of tiny parts into
intelligent machines, perhaps based on the use of trillions of
nanoscopic parallel-processing devices which make descriptions,
compare them to recorded patterns, and then exploit the memories of
all their previous experiments. Thus those new technologies could
change not merely the materials and means we use to shape our physical
environment, but also the activities we would then be able to pursue
inside whichever kind of world we make.
Now, if we return to Arthur C. Clarke's problem of predicting more
than fifty years ahead, we see that the topics Drexler treats make
this seem almost moot. For once that atom-stacking process starts,
then "only fifty years" could bring more change than all that had come
about since near-medieval times. For, it seems to me, in spite of
all we hear about modern technological revolutions, they really
haven't made such large differences in our lives over the past half
century. Did television really change our world? Surely less than
radio did, and even less than the telephone did. What about airplanes?
They merely reduced travel times from days to hours- whereas the
railroad and automobile had already made a larger change by shortening
those travel times from weeks to days! But Engines of Creation sets us
on the threshold of genuinely significant changes; nanotechnology
could have more effect on our material existence than those last two
great inventions in that domain- the replacement of sticks and
stones by metals and cements and the harnessing of electricity.
Similarly, we can compare the possible effects of artificial
intelligence on how we think- and on how we might come to think
about ourselves- with only two earlier inventions: those of language
and of writing.
We'll soon have to face some of these prospects and options. How
should we proceed to deal with them? Engines of Creation explains
how these new alternatives could be directed toward many of our most
vital human concerns: toward wealth or poverty, health or sickness,
peace or war. And Drexler offers no mere neutral catalog of
possibilities, but a multitude of ideas and proposals for how one
might start to evaluate them. Engines of Creation is the best
attempt so far to prepare us to think of what we might become,
should we persist in making new technologies.
-
MARVIN MINSKY
Donner Professor of Science
Massachusetts Institute of Technology
ACKNOWLEDGMENTS
-
THE IDEAS IN THIS BOOK have been shaped by many minds. All authors
bear an incalculable debt to earlier writers and thinkers, and the
Notes and References section provides a partial acknowledgment of my
debt. But other people have had a more immediate influence by
reading and criticizing all or part of the several papers, articles,
and draft manuscripts ancestral to the present version of this book.
Their contributions have ranged from brief letters to extensive,
detailed criticisms, suggestions, and revisions; they deserve much
of the credit for the evolution of the manuscript toward its present
form and content. I do, however, claim all blame for its remaining
failings.
Accordingly, I would like to thank Dale Amon, David Anderson,
Alice Barkan, James Bennett, David Blackwell, Kenneth Boulding, Joe
Boyle, Stephen Bridge, James Cataldo, Fred and Linda Chamberlain, Hugh
Daniel, Douglas Denholm, Peter Diamandis, Thomas Donaldson, Allan
Drexler, Hazel Drexler, Arthur Dula, Freeman Dyson, Erika Erdmann,
Robert Ettinger, Mike Federowicz, Carl Feynman, David Forrest,
Christopher Fry, Andy, Donna, Mark, and Scott Gassmann, Hazel and
Ralph Gassmann, Agnes Gregory, Roger Gregory, David Hannah, Keith
Henson, Eric Hill, Hugh Hixon, Miriam Hopkins, Joe Hopkins, Barbara
Marx Hubbard, Scott A. Jones, Arthur Kantrowitz, Manfred Karnovsky,
Pamela Keller, Tom and Mara Lansing, Jerome Lettvin, Elaine Lewis,
David Lindbergh, Spencer Love, Robert and Susan Lovell, Steve Lubar,
Arel Lucas, John Mann, Jeff MacGillivray, Bruce Mackenzie, Marvin
Minsky, Chip Morningstar, Philip Morrison, Kevin Nelson, Hugh O'Neill,
Gayle Pergamit, Gordon and Mary Peterson, Norma and Amy Peterson,
Naomi Reynolds, Carol Rosin, Phil Salin, Conrad Schneiker, Alice
Dawn Schuster, Rosemary Simpson, Leif Smith, Ray Sperber, David Sykes,
Paul Trachtman, Kevin Ulmer, Patricia Wagner, Christopher Walsh, Steve
Witham, David Woodcock, and Elisa Wynn. Since this list was compiled
from imperfect files and heaps of marked-up manuscripts, I apologize
to those I may have omitted. Further thanks are due to the members
of many audiences, at MIT and elsewhere, for asking questions that
helped me refine these ideas and their presentation.
For their help and encouragement, I would also like to thank my
agent, Norman Kurz, and my editors, James Raimes, Dave Barbor, and
Patrick Filley. Finally, for contributions of special quality and
magnitude throughout this effort, I would like to thank Mark S. Miller
and, most of all, Christine Peterson. Without her help, it would not
have been possible at all.
PART ONE
The Foundations of Foresight
-
1
Engines of Construction*
-
Protein engineering... represents*(2) the first major step toward
a more general capability for molecular engineering which would
allow us to structure matter atom by atom.
-KEVIN ULMER
Director of Exploratory Research
Genex Corporation
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COAL AND DIAMONDS, sand and computer chips, cancer and healthy
tissue: throughout history, variations in the arrangement of atoms
have distinguished the cheap from the cherished, the diseased from the
healthy. Arranged one way, atoms make up soil, air, and water;
arranged another, they make up ripe strawberries. Arranged one way,
they make up homes and fresh air; arranged another, they make up ash
and smoke.
Our ability to arrange atoms lies at the foundation of technology.
We have come far in our atom arranging, from chipping flint for
arrowheads to machining aluminum for spaceships. We take pride in
our technology, with our lifesaving drugs and desktop computers. Yet
our spacecraft are still crude, our computers are still stupid, and
the molecules in our tissues still slide into disorder, first
destroying health, then life itself. For all our advances in arranging
atoms, we still use primitive methods. With our present technology, we
are still forced to handle atoms in unruly herds.
But the laws of nature leave plenty of room for progress, and the
pressures of world competition are even now pushing us forward. For
better or for worse, the greatest technological breakthrough in
history is still to come.
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TWO STYLES OF TECHNOLOGY
-
Our modern technology builds on an ancient tradition. Thirty
thousand years ago, chipping flint was the high technology of the day.
Our ancestors grasped stones containing trillions of trillions of
atoms and removed chips containing billions of trillions of atoms to
make their axheads; they made fine work with skills difficult to
imitate today. They also made patterns on cave walls in France with
sprayed paint, using their hands as stencils. Later they made pots
by baking clay, then bronze by cooking rocks. They shaped bronze by
pounding it. They made iron, then steel, and shaped it by heating,
pounding, and removing chips.
We now cook up pure ceramics and stronger steels, but we still shape
them by pounding, chipping, and so forth. We cook up pure silicon, saw
it into slices, and make patterns on its surface using tiny stencils
and sprays of light. We call the products "chips" and we consider them
exquisitely small, at least in comparison to axheads.
Our microelectronic technology has managed to stuff machines as
powerful as the room-sized computers of the early 1950s onto a few
silicon chips in a pocket-sized computer. Engineers are now making
ever smaller devices, slinging herds of atoms at a crystal surface
to build up wires and components one tenth the width of a fine hair.
These microcircuits may be small by the standards of flint chippers,
but each transistor still holds trillions of atoms, and so-called
"microcomputers" are still visible to the naked eye. By the
standards of a newer, more powerful technology they will seem
gargantuan.
The ancient style of technology that led from flint chips to silicon
chips handles atoms and molecules in bulk; call it bulk technology.
The new technology will handle individual atoms and molecules with
control and precision; call it molecular technology. It will change
our world in more ways than we can imagine.
Microcircuits have parts measured in micrometers- that is, in
millionths of a meter- but molecules are measured in nanometers (a
thousand times smaller). We can use the terms "nanotechnology" and
"molecular technology" interchangeably to describe the new style of
technology. The engineers of the new technology will build both
nanocircuits and nanomachines.
-
MOLECULAR TECHNOLOGY TODAY
-
One dictionary*(3) definition of a machine is "any system, usually
of rigid bodies, formed and connected to alter, transmit, and direct
applied forces in a predetermined manner to accomplish a specific
objective, such as the performance of useful work." Molecular machines
fit this definition quite well.
To imagine these machines, one must first picture molecules. We
can picture atoms as beads and molecules as clumps of beads, like a
child's beads linked by snaps. In fact, chemists do sometimes
visualize molecules by building models from plastic beads (some of
which link in several directions, like the hubs in a Tinkertoy set).
Atoms are rounded like beads, and although molecular bonds are not
snaps, our picture at least captures the essential notion that bonds
can be broken and reformed.
If an atom were the size of a small marble, a fairly complex
molecule would be the size of your fist. This makes a useful mental
image, but atoms are really about 1/10,000 the size of bacteria, and
bacteria are about 1/10,000 the size of mosquitoes. (An atomic
nucleus, however, is about 1/100,000 the size of the atom itself;
the difference between an atom and its nucleus is the difference
between a fire and a nuclear reaction.)
The things around us act as they do because of the way their
molecules behave. Air holds neither its shape nor its volume because
its molecules move freely, bumping and ricocheting through open space.
Water molecules stick together as they move about, so water holds a
constant volume as it changes shape. Copper holds its shape because
its atoms stick together in regular patterns; we can bend it and
hammer it because its atoms can slip over one another while
remaining bound together. Glass shatters when we hammer it because its
atoms separate before they slip. Rubber consists of networks of kinked
molecules, like a tangle of springs. When stretched and released,
its molecules straighten and then coil again. These simple molecular
patterns make up passive substances. More complex patterns make up the
active nanomachines of living cells.
Biochemists already work with these machines, which are chiefly made
of protein, the main engineering material of living cells. These
molecular machines have relatively few atoms, and so they have lumpy
surfaces, like objects made by gluing together a handful of small
marbles. Also, many pairs of atoms are linked by bonds that can bend
or rotate, and so protein machines are unusually flexible. But like
all machines, they have parts of different shapes and sizes that do
useful work. All machines use clumps of atoms as parts. Protein
machines simply use very small clumps.
Biochemists dream of designing and building such devices, but
there are difficulties to be overcome. Engineers use beams of light to
project patterns onto silicon chips, but chemists must build much more
indirectly than that. When they combine molecules in various
sequences, they have only limited control over how the molecules join.
When biochemists need complex molecular machines, they still have to
borrow them from cells. Nevertheless, advanced molecular machines will
eventually let them build nanocircuits and nanomachines as easily
and directly as engineers now build microcircuits or washing machines.
Then progress will become swift and dramatic.
Genetic engineers are already showing the way. Ordinarily, when
chemists make molecular chains- called "polymers"- they dump molecules
into a vessel where they bump and snap together haphazardly in a
liquid. The resulting chains have varying lengths, and the molecules
are strung together in no particular order.
But in modern gene synthesis machines,*(4) genetic engineers build
more orderly polymers- specific DNA molecules- by combining
molecules in a particular order. These molecules are the nucleotides
of DNA (the letters of the genetic alphabet) and genetic engineers
don't dump them all in together. Instead, they direct the machine to
add different nucleotides in a particular sequence to spell out a
particular message. They first bond one kind of nucleotide to the
chain ends, then wash away the leftover material and add chemicals
to prepare the chain ends to bond the next nucleotide. They grow
chains as they bond on nucleotides, one at a time, in a programmed
sequence. They anchor the very first nucleotide in each chain to a
solid surface to keep the chain from washing away with its chemical
bathwater. In this way, they have a big clumsy machine in a cabinet
assemble specific molecular structures from parts a hundred million
times smaller than itself.
But this blind assembly process accidentally omits nucleotides
from some chains. The likelihood of mistakes grows as chains grow
longer. Like workers discarding bad parts before assembling a car,
genetic engineers reduce errors by discarding bad chains. Then, to
join these short chains into working genes (typically thousands of
nucleotides long), they turn to molecular machines found in bacteria.
These protein machines, called restriction enzymes, "read" certain
DNA sequences as "cut here." They read these genetic patterns by
touch, by sticking to them, and they cut the chain by rearranging a
few atoms. Other enzymes splice pieces together, reading matching
parts as "glue here"- likewise "reading" chains by selective
stickiness and splicing chains by rearranging a few atoms. By using
gene machines to write, and restriction enzymes to cut and paste,
genetic engineers can write and edit whatever DNA messages they
choose.
But by itself, DNA is a fairly worthless molecule. It is neither
strong like Kevlar, nor colorful like a dye, nor active like an
enzyme, yet it has something that industry is prepared to spend
millions of dollars to use: the ability to direct molecular machines
called ribosomes. In cells, molecular machines first transcribe DNA,
copying its information to make RNA "tapes." Then, much as old
numerically controlled machines shape metal based on instructions
stored on tape, ribosomes build proteins based on instructions
stored on RNA strands. And proteins are useful.
Proteins, like DNA, resemble strings of lumpy beads. But unlike DNA,
protein molecules fold up to form small objects able to do things.
Some are enzymes, machines that build up and tear down molecules
(and copy DNA, transcribe it, and build other proteins in the cycle of
life). Other proteins are hormones, binding to yet other proteins to
signal cells to change their behavior. Genetic engineers can produce
these objects cheaply by directing the cheap and efficient molecular
machinery inside living organisms to do the work. Whereas engineers
running a chemical plant must work with vats of reacting chemicals
(which often misarrange atoms and make noxious byproducts),
engineers working with bacteria can make them absorb chemicals,
carefully rearrange the atoms, and store a product or release it
into the fluid around them.
Genetic engineers have now programmed bacteria to make proteins
ranging from human growth hormone to rennin, an enzyme used in
making cheese. The pharmaceutical company Eli Lilly (Indianapolis)
is now marketing Humulin, human insulin molecules made by bacteria.
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EXISTING PROTEIN MACHINES
-
These protein hormones and enzymes selectively stick to other
molecules. An enzyme changes its target's structure, then moves on;
a hormone affects its target's behavior only so long as both remain
stuck together. Enzymes and hormones can be described in mechanical
terms, but their behavior is more often described in chemical terms.
But other proteins serve basic mechanical functions.*(5) Some push
and pull, some act as cords or struts, and parts of some molecules
make excellent bearings. The machinery of muscle, for instance, has
gangs of proteins that reach, grab a "rope" (also made of protein),
pull it, then reach out again for a fresh grip; whenever you move, you
use these machines. Amoebas and human cells move and change shape by
using fibers and rods that act as molecular muscles and bones. A
reversible, variable-speed motor drives bacteria through water by
turning a corkscrew-shaped propeller. If a hobbyist could build tiny
cars around such motors, several billions of billions would fit in a
pocket, and 150-lane freeways could be built through your finest
capillaries.
Simple molecular devices combine to form systems resembling
industrial machines. In the 1950s engineers developed machine tools
that cut metal under the control of a punched paper tape. A century
and a half earlier, Joseph-Marie Jacquard had built a loom that wove
complex patterns under the control of a chain of punched cards. Yet
over three billion years before Jacquard, cells had developed the
machinery of the ribosome. Ribosomes are proof that nanomachines built
of protein and RNA can be programmed to build complex molecules.
Then consider viruses. One kind, the T4 phage, acts like a
spring-loaded syringe and looks like something out of an industrial
parts catalog. It can stick to a bacterium, punch a hole, and inject
viral DNA (yes, even bacteria suffer infections). Like a conqueror
seizing factories to build more tanks, this DNA then directs the
cell's machines to build more viral DNA and syringes. Like all
organisms, these viruses exist because they are fairly stable and
are good at getting copies of themselves made.
Whether in cells or not, nanomachines obey the universal laws of
nature. Ordinary chemical bonds hold their atoms together, and
ordinary chemical reactions (guided by other nanomachines) assemble
them. Protein molecules can even join to form machines without special
help, driven only by thermal agitation and chemical forces. By
mixing viral proteins (and the DNA they serve) in a test tube,
molecular biologists have assembled working T4 viruses. This ability
is surprising: imagine putting automotive parts in a large box,
shaking it, and finding an assembled car when you look inside! Yet the
T4 virus is but one of many self-assembling structures.*(6)
Molecular biologists have taken the machinery of the ribosome apart
into over fifty separate protein and RNA molecules, and then
combined them in test tubes to form working ribosomes again.
To see how this happens, imagine different T4 protein chains
floating around in water. Each kind folds up to form a lump with
distinctive bumps and hollows, covered by distinctive patterns of
oiliness, wetness, and electric charge. Picture them wandering and
tumbling, jostled by the thermal vibrations of the surrounding water
molecules. From time to time two bounce together, then bounce apart.
Sometimes, though, two bounce together and fit, bumps in hollows, with
sticky patches matching; they then pull together and stick. In this
way protein adds to protein to make sections of the virus, and
sections assemble to form the whole.
Protein engineers will not need nanoarms and nanohands to assemble
complex nanomachines. Still, tiny manipulators will be useful and they
will be built. Just as today's engineers build machinery as complex as
player pianos and robot arms from ordinary motors, bearings, and
moving parts, so tomorrow's biochemists will be able to use protein
molecules as motors, bearings, and moving parts to build robot arms
which will themselves be able to handle individual molecules.
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DESIGNING WITH PROTEIN*(7)
-
How far off is such an ability? Steps have been taken, but much work
remains to be done. Biochemists have already mapped the structures
of many proteins. With gene machines to help write DNA tapes, they can
direct cells to build any protein they can design.*(8) But they
still don't know how to design chains that will fold up to make
proteins of the right shape and function. The forces that fold
proteins are weak, and the number of plausible ways a protein might
fold is astronomical, so designing a large protein from scratch
isn't easy.
The forces that stick proteins together to form complex machines are
the same ones that fold the protein chains in the first place. The
differing shapes and kinds of stickiness of amino acids- the lumpy
molecular "beads" forming protein chains- make each protein chain fold
up in a specific way to form an object of a particular shape.
Biochemists have learned rules that suggest how an amino acid chain
might fold, but the rules aren't very firm. Trying to predict how a
chain will fold is like trying to work a jigsaw puzzle, but a puzzle
with no pattern printed on its pieces to show when the fit is correct,
and with pieces that seem to fit together about as well (or as
badly) in many different ways, all but one of them wrong. False starts
could consume many lifetimes, and a correct answer might not even be
recognized. Biochemists using the best computer programs now available
still cannot predict how a long, natural protein chain will actually
fold, and some of them have despaired of designing protein molecules
soon.
Yet most biochemists work as scientists, not as engineers. They work
at predicting how natural proteins will fold, not at designing
proteins that will fold predictably. These tasks may sound
similar,*(9) but they differ greatly: the first is a scientific
challenge, the second is an engineering challenge. Why should
natural proteins fold in a way that scientists will find easy to
predict? All that nature requires is that they in fact fold correctly,
not that they fold in a way obvious to people.
Proteins could be designed from the start with the goal of making
their folding more predictable. Carl Pabo, writing in the journal
Nature,*(10) has suggested a design strategy based on this insight,
and some biochemical engineers have designed and built short chains of
a few dozen pieces*(11) that fold and nestle onto the surfaces of
other molecules as planned. They have designed from scratch a
protein*(12) with properties like those of melittin, a toxin in bee
venom. They have modified existing enzymes, changing their behaviors
in predictable ways.*(13) Our understanding of proteins is growing
daily.
In 1959, according to biologist Garrett Hardin,*(14) some
geneticists called genetic engineering impossible; today, it is an
industry. Biochemistry and computer-aided design are now exploding
fields, and as Frederick Blattner wrote in the journal Science,*(15)
"computer chess programs have already reached the level below the
grand master. Perhaps the solution to the protein-folding problem is
nearer than we think." William Rastetter of Genentech, writing in
Applied Biochemistry and Biotechnology,*(16) asks, "How far off is
de novo enzyme design and synthesis? Ten, fifteen years?" He
answers, "Perhaps not that long."
Forrest Carter of the U.S. Naval Research Laboratory, Ari Aviram and
Philip Seiden of IBM, Kevin Ulmer of Genex Corporation, and other
researchers in university and industrial laboratories around the globe
have already begun theoretical work and experiments aimed at
developing molecular switches, memory devices, and other structures
that could be incorporated into a protein-based computer. The U.S.
Naval Research Laboratory has held two international workshops on
molecular electronic devices,*(17) and a meeting sponsored by the U.S.
National Science Foundation has recommended support for basic
research*(18) aimed at developing molecular computers. Japan has
reportedly begun a multimillion-dollar program aimed at developing
self-assembling molecular motors and computers, and VLSI Research
Inc.,*(19) of San Jose, reports that "It looks like the race to
bio-chips [another term for molecular electronic systems] has
already started. NEC, Hitachi, Toshiba, Matsushita, Fujitsu,
Sanyo-Denki and Sharp have commenced full-scale research efforts on
bio-chips for bio-computers."
Biochemists have other reasons to want to learn the art of protein
design. New enzymes promise to perform dirty, expensive chemical
processes more cheaply and cleanly, and novel proteins will offer a
whole new spectrum of tools to biotechnologists. We are already on the
road to protein engineering, and as Kevin Ulmer notes in the quote
from Science that heads this chapter, this road leads "toward a more
general capability for molecular engineering which would allow us to
structure matter atom by atom."
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SECOND-GENERATION NANOTECHNOLOGY
-
Despite its versatility, protein has shortcomings as an
engineering material. Protein machines quit when dried, freeze when
chilled, and cook when heated. We do not build machines of flesh,
hair, and gelatin; over the centuries, we have learned to use our
hands of flesh and bone to build machines of wood, ceramic, steel, and
plastic. We will do likewise in the future. We will use protein
machines to build nanomachines of tougher stuff than protein.
As nanotechnology moves beyond reliance on proteins, it will grow
more ordinary from an engineer's point of view. Molecules will be
assembled like the components of an erector set, and well-bonded parts
will stay put. Just as ordinary tools can build ordinary machines from
parts, so molecular tools will bond molecules together to make tiny
gears, motors, levers, and casings, and assemble them to make
complex machines.
Parts containing only a few atoms will be lumpy, but engineers can
work with lumpy parts if they have smooth bearings to support them.
Conveniently enough, some bonds between atoms make fine bearings; a
part can be mounted by means of a single chemical bond*(20) that
will let it turn freely and smoothly. Since a bearing can be made
using only two atoms (and since moving parts need have only a few
atoms), nanomachines can indeed have mechanical components of
molecular size.
How will these better machines be built? Over the years, engineers
have used technology to improve technology. They have used metal tools
to shape metal into better tools, and computers to design and
program better computers. They will likewise use protein
nanomachines to build better nanomachines. Enzymes show the way:
they assemble large molecules by "grabbing" small molecules from the
water around them, then holding them together so that a bond forms.
Enzymes assemble DNA, RNA, proteins, fats, hormones, and chlorophyll
in this way- indeed, virtually the whole range of molecules found in
living things.
Biochemical engineers, then, will construct new enzymes to
assemble new patterns of atoms. For example, they might make an
enzyme-like machine which will add carbon atoms to a small spot, layer
on layer. If bonded correctly, the atoms will build up to form a fine,
flexible diamond fiber*(21) having over fifty times as much strength
as the same weight of aluminum. Aerospace companies will line up to
buy such fibers by the ton to make advanced composites. (This shows
one small reason why military competition will drive molecular
technology forward, as it has driven so many fields in the past.)
But the great advance will come when protein machines are able to
make structures more complex than mere fibers. These programmable
protein machines will resemble ribosomes programmed by RNA, or the
older generation of automated machine tools programmed by punched
tapes. They will open a new world of possibilities, letting
engineers escape the limitations of proteins to build rugged,
compact machines with straightforward designs.
Engineered proteins will split and join molecules as enzymes do.
Existing proteins bind a variety of smaller molecules, using them as
chemical tools; newly engineered proteins will use all these tools and
more.
Further, organic chemists have shown that chemical reactions can
produce remarkable results even without nanomachines to guide the
molecules. Chemists have no direct control over the tumbling motions
of molecules in a liquid, and so the molecules are free to react in
any way they can, depending on how they bump together. Yet chemists
nonetheless coax reacting molecules*(22) to form regular structures
such as cubic and dodecahedral molecules, and to form unlikely-seeming
structures such as molecular rings with highly strained bonds.
Molecular machines will have still greater versatility in
bondmaking, because they can use similar molecular motions to make
bonds, but can guide these motions in ways that chemists cannot.
Indeed, because chemists cannot yet direct molecular motions, they
can seldom assemble complex molecules according to specific plans. The
largest molecules they can make with specific, complex patterns are
all linear chains. Chemists form these patterns (as in gene
machines) by adding molecules in sequence, one at a time, to a growing
chain. With only one possible bonding site per chain, they can be sure
to add the next piece in the right place.
But if a rounded, lumpy molecule has (say) a hundred hydrogen
atoms on its surface, how can chemists split off just one particular
atom (the one five up and three across from the bump on the front)
to add something in its place? Stirring simple chemicals together will
seldom do the job, because small molecules can seldom select
specific places to react with a large molecule. But protein machines
will be more choosy.
A flexible, programmable protein machine will grasp a large molecule
(the workpiece) while bringing a small molecule up against it in
just the right place. Like an enzyme, it will then bond the
molecules together. By bonding molecule after molecule to the
workpiece, the machine will assemble a larger and larger structure
while keeping complete control of how its atoms are arranged. This
is the key ability that chemists have lacked.
Like ribosomes, such nanomachines can work under the direction of
molecular tapes. Unlike ribosomes, they will handle a wide variety
of small molecules (not just amino acids) and will join them to the
workpiece anywhere desired, not just to the end of a chain. Protein
machines will thus combine the splitting and joining abilities of
enzymes with the programmability of ribosomes. But whereas ribosomes
can build only the loose folds of a protein, these protein machines
will build small, solid objects of metal, ceramic, or diamond-
invisibly small, but rugged.
Where our fingers of flesh are likely to bruise or burn, we turn
to steel tongs. Where protein machines are likely to crush or
disintegrate, we will turn to nanomachines made of tougher stuff.
-
UNIVERSAL ASSEMBLERS
-
These second-generation nanomachines- built of more than just
proteins- will do all that proteins can do, and more.*(23) In
particular, some will serve as improved devices for assembling
molecular structures. Able to tolerate acid or vacuum, freezing or
baking, depending on design, enzyme-like second-generation machines
will be able to use as "tools" almost any of the reactive molecules
used by chemists- but they will wield them with the precision of
programmed machines. They will be able to bond atoms together in
virtually any stable pattern, adding a few at a time to the surface of
a workpiece until a complex structure is complete. Think of such
nanomachines as assemblers.*(24)
Because assemblers will let us place atoms in almost any
reasonable arrangement (as discussed in the Notes),*(25) they will let
us build almost anything that the laws of nature allow to exist. In
particular, they will let us build almost anything we can design-
including more assemblers. The consequences of this will be
profound, because our crude tools have let us explore only a small
part of the range of possibilities that natural law permits.
Assemblers will open a world of new technologies.
Advances in the technologies of medicine, space, computation, and
production- and warfare- depend on our ability to arrange atoms.
With assemblers, we will be able to remake our world or destroy it. So
at this point it seems wise to step back and look at the prospect as
clearly as we can, so we can be sure that assemblers and
nanotechnology are not a mere futurological mirage.
-
NAILING DOWN CONCLUSIONS
-
In everything I have been describing, I have stuck closely to the
demonstrated facts of chemistry and molecular biology. Still, people
regularly raise certain questions rooted in physics and biology. These
deserve more direct answers.
-Will the uncertainty principle of quantum physics make molecular
machines unworkable?
This principle states (among other things) that particles can't be
pinned down in an exact location for any length of time. It limits
what molecular machines can do, just as it limits what anything else
can do. Nonetheless, calculations show that the uncertainty
principle places few important limits on how well atoms can be held in
place, at least for the purposes outlined here. The uncertainty
principle makes electron positions quite fuzzy, and in fact this
fuzziness determines the very size and structure of atoms. An atom
as a whole, however, has a comparatively definite position set by
its comparatively massive nucleus. If atoms didn't stay put fairly
well, molecules would not exist. One needn't study quantum mechanics
to trust these conclusions, because molecular machines in the cell
demonstrate that molecular machines work.
-Will the molecular vibrations of heat make molecular machines
unworkable or too unreliable for use?
Thermal vibrations will cause greater problems than will the
uncertainty principle, yet here again existing molecular machines
directly demonstrate that molecular machines can work at ordinary
temperatures. Despite thermal vibrations, the DNA-copying machinery in
some cells*(26) makes less than one error in 100,000,000,000
operations. To achieve this accuracy, however, cells use machines
(such as the enzyme DNA polymerase I) that proofread the copy and
correct errors. Assemblers may well need similar error-checking and
error-correcting abilities, if they are to produce reliable results.
-Will radiation disrupt molecular machines and render them unusable?
High-energy radiation can break chemical bonds and disrupt molecular
machines. Living cells once again show that solutions exist: they
operate for years by repairing and replacing radiation-damaged
parts.*(27) Because individual machines are so tiny, however, they
present small targets for radiation and are seldom hit. Still, if a
system of nanomachines must be reliable, then it will have to tolerate
a certain amount of damage, and damaged parts must regularly be
repaired or replaced. This approach to reliability is well known to
designers of aircraft and spacecraft.
-Since evolution has failed to produce assemblers, does this show
that they are either impossible or useless?
The earlier questions were answered in part by pointing to the
working molecular machinery of cells. This makes a simple and powerful
case that natural law permits small clusters of atoms to behave as
controlled machines, able to build other nanomachines. Yet despite
their basic resemblance to ribosomes, assemblers will differ from
anything found in cells; the things they do- while consisting of
ordinary molecular motions and reactions- will have novel results.
No cell, for example, makes diamond fiber.
The idea that new kinds of nanomachinery will bring new, useful
abilities may seem startling: in all its billions of years of
evolution, life has never abandoned*(28) its basic reliance on protein
machines. Does this suggest that improvements are impossible,
though? Evolution progresses through small changes, and evolution of
DNA cannot easily replace DNA. Since the DNA/RNA/ribosome system is
specialized to make proteins, life has had no real opportunity to
evolve an alternative. Any production manager can well appreciate
the reasons; even more than a factory, life cannot afford to shut down
to replace its old systems.
Improved molecular machinery should no more surprise us than alloy
steel being ten times stronger than bone, or copper wires transmitting
signals a million times faster than nerves. Cars outspeed cheetahs,
jets outfly falcons, and computers already outcalculate
head-scratching humans. The future will bring further examples of
improvements on biological evolution, of which second-generation
nanomachines will be but one.
In physical terms, it is clear enough why advanced assemblers will
be able to do more than existing protein machines. They will be
programmable like ribosomes, but they will be able to use a wider
range of tools than all the enzymes in a cell put together. Because
they will be made of materials far more strong, stiff, and stable than
proteins, they will be able to exert greater forces, move with greater
precision, and endure harsher conditions. Like an industrial robot
arm- but unlike anything in a living cell- they will be able to rotate
and move molecules in three dimensions under programmed control,
making possible the precise assembly of complex objects. These
advantages will enable them to assemble a far wider range of molecular
structures than living cells have done.
-Is there some special magic about life, essential to making
molecular machinery work?
One might doubt that artificial nanomachines could even equal the
abilities of nanomachines in the cell, if there were reason to think
that cells contained some special magic that makes them work. This
idea is called "vitalism." Biologists have abandoned it because they
have found chemical and physical explanations for every aspect of
living cells yet studied, including their motion, growth, and
reproduction. Indeed, this knowledge is the very foundation of
biotechnology.
Nanomachines floating in sterile test tubes, free of cells, have
been made to perform all the basic sorts of activities that they
perform inside living cells. Starting with chemicals that can be
made from smoggy air, biochemists have built working protein
machines without help from cells. R. B. Merrifield, for example,
used chemical techniques*(29) to assemble simple amino acids to make
bovine pancreatic ribonuclease, an enzymatic device that
disassembles RNA molecules. Life is special in structure, in behavior,
and in what it feels like from the inside to be alive, yet the laws of
nature that govern the machinery of life also govern the rest of the
universe.
-The case for the feasibility of assemblers and other nanomachines
may sound firm, but why not just wait and see whether they can be
developed?
Sheer curiosity seems reason enough to examine the possibilities
opened by nanotechnology, but there are stronger reasons. These
developments will sweep the world within ten to fifty years- that
is, within the expected lifetimes of ourselves or our families. What
is more, the conclusions of the following chapters suggest that a
wait-and-see policy would be very expensive- that it would cost many
millions of lives, and perhaps end life on Earth.
Is the case for the feasibility of nanotechnology and assemblers
firm enough that they should be taken seriously? It seems so,
because the heart of the case rests on two well-established facts of
science and engineering. These are (1) that existing molecular
machines serve a range of basic functions, and (2) that parts
serving these basic functions can be combined to build complex
machines. Since chemical reactions can bond atoms together in
diverse ways, and since molecular machines can direct chemical
reactions according to programmed instructions, assemblers
definitely are feasible.
-
NANOCOMPUTERS
-
Assemblers will bring one breakthrough of obvious and basic
importance: engineers will use them to shrink the size and cost of
computer circuits and speed their operation by enormous factors.
With today's bulk technology, engineers make patterns on silicon
chips by throwing atoms and photons at them, but the patterns remain
flat and molecular-scale flaws are unavoidable. With assemblers,
however, engineers will build circuits in three dimensions, and
build to atomic precision. The exact limits of electronic technology
today remain uncertain because the quantum behavior of electrons in
complex networks of tiny structures presents complex problems, some of
them resulting directly from the uncertainty principle. Whatever the
limits are, though, they will be reached with the help of assemblers.
The fastest computers will use electronic effects, but the
smallest may not. This may seem odd, yet the essence of computation
has nothing to do with electronics. A digital computer is a collection
of switches able to turn one another on and off. Its switches start in
one pattern (perhaps representing 2 + 2), then switch one another into
a new pattern (representing 4), and so on. Such patterns can represent
almost anything. Engineers build computers from tiny electrical
switches connected by wires simply because mechanical switches
connected by rods or strings would be big, slow, unreliable, and
expensive, today.
The idea of a purely mechanical computer is scarcely new. In England
during the mid-1800s, Charles Babbage*(30) invented a mechanical
computer built of brass gears; his co-worker Augusta Ada, the Countess
of Lovelace, invented computer programming. Babbage's endless
redesigning of the machine, problems with accurate manufacturing,
and opposition from budget-watching critics (some doubting the
usefulness of computers!), combined to prevent its completion.
In this tradition, Danny Hillis and Brian Silverman of the MIT
Artificial Intelligence Laboratory built a special-purpose
mechanical computer able to play tic-tac-toe. Yards on a side, full of
rotating shafts and movable frames that represent the state of the
board and the strategy of the game, it now stands in the Computer
Museum in Boston. It looks much like a large ball-and-stick
molecular model, for it is built of Tinkertoys.
Brass gears and Tinkertoys make for big, slow computers. With
components a few atoms wide, though, a simple mechanical computer
would fit within 1/100 of a cubic micron, many billions of times
more compact than today's so-called microelectronics. Even with a
billion bytes of storage, a nanomechanical computer could fit in a box
a micron wide,*(31) about the size of a bacterium. And it would be
fast. Although mechanical signals*(32) move about 100,000 times slower
than the electrical signals in today's machines, they will need to
travel only 1/1,000,000 as far, and thus will face less delay. So a
mere mechanical computer will work faster than the electronic
whirlwinds of today.
Electronic nanocomputers will likely be thousands of times faster
than electronic microcomputers- perhaps hundreds of thousands of times
faster, if a scheme proposed by Nobel Prize-winning physicist
Richard Feynman*(33) works out. Increased speed through decreased size
is an old story in electronics.
-
DISASSEMBLERS
-
Molecular computers will control molecular assemblers, providing the
swift flow of instructions needed to direct the placement of vast
numbers of atoms. Nanocomputers with molecular memory devices will
also store data generated by a process that is the opposite of
assembly.
Assemblers will help engineers synthesize things; their relatives,
disassemblers, will help scientists and engineers analyze things.
The case for assemblers rests on the ability of enzymes and chemical
reactions to form bonds, and of machines to control the process. The
case for disassemblers rests on the ability of enzymes and chemical
reactions to break bonds, and of machines to control the process.
Enzymes, acids, oxidizers, alkali metals, ions, and reactive groups of
atoms called free radicals- all can break bonds and remove groups of
atoms. Because nothing is absolutely immune to corrosion, it seems
that molecular tools will be able to take anything apart, a few
atoms at a time. What is more, a nanomachine could (at need or
convenience) apply mechanical force as well, in effect prying groups
of atoms free.
A nanomachine able to do this, while recording what it removes layer
by layer, is a disassembler.*(34) Assemblers, disassemblers, and
nanocomputers will work together. For example, a nanocomputer system
will be able to direct the disassembly of an object, record its
structure, and then direct the assembly of perfect copies. And this
gives some hint of the power of nanotechnology.
-
THE WORLD MADE NEW
-
Assemblers will take years to emerge, but their emergence seems
almost inevitable: Though the path to assemblers has many steps,
each step will bring the next in reach, and each will bring
immediate rewards. The first steps have already been taken, under
the names of "genetic engineering" and "biotechnology." Other paths to
assemblers seem possible. Barring worldwide destruction or worldwide
controls, the technology race will continue whether we wish it or not.
And as advances in computer-aided design speed the development of
molecular tools, the advance toward assemblers will quicken.
To have any hope of understanding our future, we must understand the
consequences of assemblers, disassemblers, and nanocomputers. They
promise to bring changes as profound as the industrial revolution,
antibiotics, and nuclear weapons all rolled up in one massive
breakthrough. To understand a future of such profound change, it makes
sense to seek principles of change that have survived the greatest
upheavals of the past. They will prove a useful guide.
2
The Principles of Change
-
Think of the design process*(35) as involving first the generation
of alternatives and then the testing of these alternatives against a
whole array of requirements and constraints.
-HERBERT A. SIMON
-
MOLECULAR ASSEMBLERS will bring a revolution without parallel
since the development of ribosomes, the primitive assemblers in the
cell. The resulting nanotechnology can help life spread beyond
Earth- a step without parallel since life spread beyond the seas. It
can help mind emerge in machines- a step without parallel since mind
emerged in primates. And it can let our minds renew and remake our
bodies- a step without any parallel at all.
These revolutions will bring dangers and opportunities too vast
for the human imagination to grasp. Yet the principles of change
that have applied to molecules, cells, beasts, minds, and machines
should endure even in an age of biotechnology, nanomachines, and
artificial minds. The same principles that have applied at sea, on
land, and in the air should endure as we spread Earth's life toward
the stars. Understanding the enduring principles of change will help
us understand the potential for good and ill in the new technologies.
-
ORDER FROM CHAOS
-
Order can emerge from chaos without anyone's giving orders:
orderly crystals condensed from formless interstellar gas long
before Sun, Earth, or life appeared. Chaos also gives rise to a
crystalline order under more familiar circumstances. Imagine a
molecule- perhaps regular in form, or perhaps lopsided and knobby like
a ginger root. Now imagine a vast number of such molecules moving
randomly in a liquid, tumbling and jostling like drunkards in
weightlessness in the dark. Imagine the liquid evaporating and
cooling, forcing the molecules closer together and slowing them
down. Will these randomly moving, oddly shaped molecules simply gather
in disordered heaps? Generally not. They will usually settle into a
crystalline pattern, each neatly nestled against its neighbors,
forming rows and columns as perfect as a checkerboard, though often
more complex.
This process involves neither magic nor some special property of
molecules and quantum mechanical forces. It does not even require
the special matching shapes that enable protein molecules to
self-assemble into machines. Marbles of uniform size, if placed in a
tray and shaken, also settle into a regular pattern.
Crystals grow by trial and the removal of error, by variation and
selection. No tiny hands assemble them. A crystal can begin with a
chance clumping of molecules: the molecules wander, bump, and clump at
random, but clumps stick best when packed in the right crystalline
pattern. Other molecules then strike this first, tiny crystal. Some
bump in the wrong position or orientation; they stick poorly and shake
loose again. Others happen to bump properly; they stick better and
often stay. Layer builds on layer, extending the crystalline
pattern. Though the molecules bump at random, they do not stick at
random. Order grows from chaos through variation and selection.
-
EVOLVING MOLECULES
-
In crystal growth, each layer forms a template for the next. Uniform
layers accumulate to form a solid block.
In cells, strands of DNA or RNA can serve as templates too, aided by
enzymes that act as molecular copying machines. But the subunits of
nucleic acid strands can be arranged in many different sequences,
and a template strand can separate from its copy. Both strand and
copy*(36) can then be copied again. Biochemist Sol Spiegelman*(37) has
used a copying machine (a protein from a virus) in test tube
experiments. In a simple, lifeless environment, it duplicates RNA
molecules.
Picture a strand of RNA floating in a test tube together with
copying machines and RNA subunits. The strand tumbles and writhes
until it bumps into a copying machine in the right position to
stick. Subunits bump around until one of the right kind meets the
copying machine in the right position to match the template strand. As
matching subunits chance to fall into position, the machine seizes
them and bonds them to the growing copy; though subunits bump
randomly, the machine bonds selectively. Finally the machine, the
template, and the copy separate.
In the terminology of Oxford zoologist Richard Dawkins,*(38)
things that give rise to copies of themselves are called
replicators. In this environment, RNA molecules qualify: a single
molecule soon becomes two, then four, eight, sixteen, thirty-two,
and so forth, multiplying exponentially. Later, the replication rate
levels off: the fixed stock of protein machines can churn out RNA
copies only so fast, no matter how many template molecules vie for
their services. Later still, the raw materials for making RNA
molecules become scarce and replication starves to a halt. The
exploding population of molecules reaches a limit to growth and
stops reproducing.
The copying machines, however, often miscopy an RNA strand,
inserting, deleting, or mismatching a subunit. The resulting mutated
strand then differs in length or subunit sequence. Such changes are
fairly random, and changes accumulate as miscopied molecules are again
miscopied. As the molecules proliferate, they begin to grow
different from their ancestors and from each other. This might seem
a recipe for chaos.
Biochemists have found that differing RNA molecules replicate at
differing rates, depending on their lengths and subunit patterns.
Descendants of the swifter replicators naturally grow more common.
Indeed, if one kind replicates just 10 percent more rapidly than its
siblings, then after one hundred generations, each of the faster
kind gives rise to 1,000 times as many descendants. Small
differences in exponential growth pile up exponentially.
When a test tube runs out of subunits, an experimenter can sample
its RNA and "infect" a fresh tube. The process begins again and the
molecules that dominated the first round of competition begin with a
head start. More small changes appear, building over time into large
changes. Some molecules replicate faster, and their kind dominates the
mix. When resources run out, the experimenter can sample the RNA and
start again (and again, and again), holding conditions stable.
This experiment reveals a natural process: no matter what RNA
sequences the experimenter starts with, the seeming chaos of random
errors and biased copying brings forth one kind of RNA molecule
(give or take some copying errors). Its typical version has a known,
well-defined sequence of 220 subunits. It is the best RNA replicator
in this environment, so it crowds out the others and stays.
Prolonged copying, miscopying, and competition always bring about
the same result, no matter what the length or pattern of the RNA
molecule that starts the process. Though no one could have predicted
this winning pattern, anyone can see that change and competition
will tend to bring forth a single winner. Little else could happen
in so simple a system. If these replicators affected one another
strongly (perhaps by selectively attacking or helping one another),
then the result could resemble a more complex ecology. As it is,
they just compete for a resource.
A variation on this example shows us something else: RNA molecules
adapt differently to different environments. A molecular machine
called a ribonuclease grabs RNA molecules having certain sequences
of exposed subunits and cuts them in two. But RNA molecules, like
proteins, fold in patterns that depend on their sequences, and by
folding the right way they can protect their vulnerable spots.
Experimenters find that RNA molecules evolve to sacrifice swift
replication for better protection when ribonuclease is around.
Again, a best competitor emerges.
Notice that biological terms have crept into this description: since
the molecules replicate, the word "generation" seems right;
molecules "descended" from a common "ancestor" are "relatives," and
the words "growth," "reproduction," "mutation," and "competition" also
seem right. Why is this? Because these molecules copy themselves
with small variations, as do the genes of living organisms. When
varying replicators have varying successes, the more successful tend
to accumulate. This process, wherever it occurs, is "evolution."
In this test tube example we can see evolution stripped to its
bare essentials, free of the emotional controversy surrounding the
evolution of life. The RNA replicators and protein copying machines
are well-defined collections of atoms obeying well-understood
principles and evolving in repeatable laboratory conditions.
Biochemists can make RNA and protein from off-the-shelf chemicals,
without help from life.
Biochemists borrow these copying machines from a kind of virus
that infects bacteria and uses RNA as its genetic material. These
viruses survive by entering a bacterium, getting themselves copied
using its resources, and then escaping to infect new bacteria.
Miscopying of viral RNA produces mutant viruses, and viruses that
replicate more successfully grow more common; this is evolution by
natural selection, apparently called "natural" because it involves
nonhuman parts of nature. But unlike the test tube RNA, viral RNA must
do more than just replicate itself as a bare molecule. Successful
viral RNA must also direct bacterial ribosomes to build protein
devices that let it first escape from the old bacterium, then
survive outside, and finally enter a new one. This additional
information makes viral RNA molecules about 4,500 subunits long.
To replicate successfully, the DNA of large organisms must do even
more, directing the construction of tens of thousands of different
protein machines and the development of complex tissues and organs.
This requires thousands of genes coded in millions to billions of
DNA subunits. Nevertheless, the essential process of evolution by
variation and selection remains the same in the test tube, in viruses,
and far beyond.
-
EXPLAINING ORDER
-
There are at least three ways to explain the structure of an evolved
population of molecular replicators, whether test tube RNA, viral
genes, or human genes. The first kind of explanation is a blow-by-blow
account of their histories: how specific mutations occurred and how
they spread. This is impossible without recording all the molecular
events, and such a record would in any event be immensely tedious.
The second kind of explanation resorts to a somewhat misleading
word: purpose. In detail, the molecules simply change haphazardly
and replicate selectively. Yet stepping back from the process, one
could describe the outcome by imagining that the surviving molecules
have changed to "achieve the goal" of replication. Why do RNA
molecules that evolved under the threat of ribonuclease fold as they
do? Because of a long and detailed history, of course, but the idea
that "they want to avoid attack and survive to replicate" would
predict the same result. The language of purpose makes useful
shorthand (try discussing human action without it!), but the
appearance of purpose need not result from the action of a mind. The
RNA example shows this quite neatly.
The third (and often best) kind of explanation- in terms of
evolution- says that order emerges through the variation and selection
of replicators. A molecule folds in a particular way because it
resembles ancestors that multiplied more successfully (by avoiding
attack, etc.), and left descendants including itself. As Richard
Dawkins points out,*(39) the language of purpose (if used carefully)
can be translated into the language of evolution.
Evolution attributes patterns of success to the elimination of
unsuccessful changes. It thus explains a positive as the result of a
double negative- an explanation of a sort that seems slightly
difficult to grasp. Worse, it explains something visible
(successful, purposeful entities) in terms of something invisible
(unsuccessful entities that have vanished). Because only successful
beasts have littered the landscape with the bones of their
descendants, the malformed failures of the past haven't even left many
fossils.
The human mind tends to focus on the visible, seeking positive
causes for positive results, an ordering force behind orderly results.
Yet through reflection we can see that this great principle has
changed our past and will shape our future: Evolution proceeds by
the variation and selection of replicators.
-
EVOLVING ORGANISMS
-
The history of life is the history of an arms race based on
molecular machinery. Today, as this race approaches a new and
swifter phase, we need to be sure we understand just how deeply rooted
evolution is. In a time when the idea of biological evolution is often
slighted in the schools and sometimes attacked, we should remember
that the supporting evidence is as solid as rock and as common as
cells.
In pages of stone, the Earth itself has recorded the history of
life. On lake bottoms and seabed, shells, bones, and silt have
piled, layer on layer. Sometimes a shifting current or a geological
upheaval has washed layers away; otherwise they have simply
deepened. Early layers, buried deep, have been crushed, baked,
soaked in mineral waters, and turned to stone.
For centuries, geologists have studied rocks to read Earth's past.
Long ago, they found seashells high in the crushed and crumpled rock
of mountain ranges. By 1785- seventy-four years before Darwin's
detested book*(40)- James Hutton had concluded that seabed mud had
been pressed to stone and raised skyward by forces not yet understood.
What else could geologists think, unless nature itself had lied?
They saw that fossil bones and shells differed from layer to
layer. They saw that shells in layers here matched shells in layers
there, though the layers might lie deep beneath the land between. They
named layers (A, B, C, D..., or Osagian, Meramecian, Lower Chesterian,
Upper Chesterian...), and used characteristic fossils to trace rock
layers. The churning of Earth's crust has nowhere left a complete
sequence of layers exposed, yet geologists finding A, B, C, D, E in
one place, C, D, E, F, G, H, I, J in another and J, K, L somewhere
else could see that A preceded L. Petroleum geologists (even those who
care nothing for evolution or its implications) still use such fossils
to date rock layers and to trace layers from one drill site to
another.
Scientists came to the obvious conclusion. Just as sea species today
live in broad areas, so did species in years gone by. Just as layer
piles on top of layer today, so did they then. Similar shells in
similar layers mark sediments laid down in the same age. Shells change
from layer to layer because species changed from age to age. This is
what geologists found written in shells and bones on pages of stone.
The uppermost layers of rock contain bones of recent animals, deeper
layers contain bones of animals now extinct. Still earlier layers show
no trace of any modern species. Below mammal bones lie dinosaur bones;
in older layers lie amphibian bones, then shells and fish bones, and
then no bones or shells at all. The oldest fossil-bearing rocks bear
the microscopic traces of single cells.
Radioactive dating shows these oldest traces to be several billion
years old. Cells more complex than bacteria date to little more than
one billion years ago. The history of worms, fish, amphibians,
reptiles, and mammals spans hundreds of millions of years.
Human-like bones date back several million years. The remains of
civilizations date back several thousand.
In three billion years, life evolved from single cells able to
soak up chemicals to collections of cells embodying minds able to soak
up ideas. Within the last century, technology has evolved from the
steam locomotive and electric light to the spaceship and the
electronic computer- and computers are already being taught to read
and write. With mind and technology, the rate of evolution has
jumped a millionfold or more.
-
Another Route Back
-
The book of stone records the forms of long-dead organisms, yet
living cells also carry records, genetic texts only now being read. As
with the ideas of geology, the essential ideas of evolution were known
before Darwin*(41) had set pen to paper.
In lamp-lit temples and monasteries, generations of scribes copied
and recopied manuscripts. Sometimes they miscopied words and
sentences- whether by accident, by perversity, or by order of the
local ruler- and as the manuscripts replicated, aided by these human
copying machines, errors accumulated. The worst errors might be caught
and removed, and famous passages might survive unchanged, but
differences grew.
Ancient books seldom exist in their original versions. The oldest
copies are often centuries younger than the lost originals.
Nonetheless, from differing copies with differing errors, scholars can
reconstruct versions closer to the original.
They compare texts. They can trace lines of descent from common
ancestors because unique patterns of errors betray copying from a
common source. (Schoolteachers know this: identical right answers
aren't a tipoff- unless on an essay test- but woe to students
sitting side by side who turn in tests with identical mistakes!) Where
all surviving copies agree, scholars can assume that the original copy
(or at least the last shared ancestor of the survivors) held the
same words. Where survivors differ, scholars study copies that
descended separately from a distant ancestor, because areas of
agreement then indicate a common origin in the ancestral version.
Genes resemble manuscripts written in a four-letter alphabet. Much
as a message can take many forms in ordinary language (restating an
idea using entirely different words is no great strain), so
different genetic wording can direct the construction of identical
protein molecules. Moreover, protein molecules with different design
details can serve identical functions. A collection of genes in a cell
is like a whole book, and genes- like old manuscripts- have been
copied and recopied by inaccurate scribes.
Like scholars studying ancient texts, biologists generally work with
modern copies of their material (with, alas, no biological Dead Sea
Scrolls from the early days of life). They compare organisms with
similar appearances (lions and tigers, horses and zebras, rats and
mice) and find that they give similar answers to the essay questions
in their genes and proteins. The more two organisms differ (lions
and lizards, humans and sunflowers), the more these answers differ,
even among molecular machines serving identical functions. More
telling still, similar animals make the same mistakes- all primates,
for example, lack enzymes for making vitamin C, an omission shared
by only two other known mammals, the guinea pig and the fruit bat.
This suggests that we primates have copied our genetic answers from
a shared source, long ago.
The same principle that shows the lines of descent of ancient
texts (and that helps correct their copying errors) thus also
reveals the lines of descent of modern life. Indeed, it indicates that
all known life shares a common ancestor.
-
The Rise of the Replicators
-
The first replicators on Earth evolved abilities beyond those
possible to RNA molecules replicating in test tubes. By the time
they reached the bacterial stage, they had developed the "modern"
system of using DNA, RNA, and ribosomes to construct protein.
Mutations then changed not only the replicating DNA itself, but
protein machines and the living structures they build and shape.
Teams of genes shaped ever more elaborate cells, then guided the
cellular cooperation that formed complex organisms. Variation and
selection favored teams of genes that shaped beasts with protective
skins and hungry mouths, animated by nerve and muscle, guided by eye
and brain. As Richard Dawkins puts it,*(42) genes built ever more
elaborate survival machines to aid their own replication.
When dog genes replicate, they often shuffle with those of other
dogs that have been selected by people, who then select which
puppies to keep and breed. Over the millennia, people have molded
wolf-like beasts into greyhounds, toy poodles, dachshunds, and Saint
Bernards. By selecting which genes survive, people have reshaped
dogs in both body and temperament. Human desires have defined
success for dog genes; other pressures have defined success for wolf
genes.
Mutation and selection of genes has, through long ages, filled the
world with grass and trees, with insects, fish, and people. More
recently, other things have appeared and multiplied- tools, houses,
aircraft, and computers. And like the lifeless RNA molecules, this
hardware has evolved.
-
EVOLVING TECHNOLOGY
-
As the stone of Earth records the emergence of ever more complex and
capable forms of life, so the relics and writings of humanity record
the emergence of ever more complex and capable forms of hardware.
Our oldest surviving hardware is itself stone, buried with the fossils
of our ancestors; our newest hardware orbits overhead.
Consider for a moment the hybrid ancestry of the space shuttle. On
its aircraft side, it descends from the aluminum jets of the
sixties, which themselves sprang from a line stretching back through
the aluminum prop planes of World War II, to the wood-and-cloth
biplanes of World War I, to the motorized gliders of the Wright
brothers, to toy gliders and kites. On its rocket side, the shuttle
traces back to Moon rockets, to military missiles, to last century's
artillery rockets ("and the rocket's red glare..."), and finally to
fireworks and toys. This aircraft/rocket hybrid flies, and by
varying components and designs, aerospace engineers will evolve
still better ones.
Engineers speak of "generations" of technology; Japan's
"fifth-generation" computer project shows how swiftly some
technologies grow and spawn. Engineers speak of "hybrids," of
"competing technologies," and of their "proliferation." IBM Director
of Research Ralph E. Gomory emphasizes the evolutionary nature of
technology, writing that "technology development is much more
evolutionary and much less revolutionary or breakthrough-oriented than
most people imagine." (Indeed, even breakthroughs as important as
molecular assemblers will develop through many small steps.) In the
quote that heads this chapter, Professor Herbert A. Simon of
Carnegie-Mellon University urges us to "think of the design process as
involving first the generation of alternatives and then the testing of
these alternatives against a whole army of requirements and
constraints." Generation and testing of alternatives is synonymous
with variation and selection.
Sometimes various alternatives already exist. In "One Highly Evolved
Toolbox," in The Next Whole Earth Catalog,*(43) J. Baldwin writes:
"Our portable shop has been evolving for about twenty years now.
There's nothing really very special about it except that a
continuing process of removing obsolete or inadequate tools and
replacing them with more suitable ones has resulted in a collection
that has become a thing-making system rather than a pile of hardware."
Baldwin uses the term "evolving" accurately. Invention and
manufacture have for millennia generated variations in tool designs,
and Baldwin has winnowed the current crop by competitive selection,
keeping those that work best with his other tools to serve his
needs. Through years of variation and selection, his system evolved- a
process he highly recommends. Indeed, he urges that one never try to
plan out the purchase of a complete set of tools. Instead, he urges
buying the tools one often borrows, tools selected not by theory but
by experience.
Technological variations are often deliberate, in the sense that
engineers are paid to invent and test. Still, some novelties are sheer
accident, like the discovery of a crude form of Teflon in a cylinder
supposedly full of tetrafluoroethylene gas: with its valve open, it
remained heavy; when it was sawed open, it revealed a strange, waxy
solid. Other novelties have come from systematic blundering. Edison
tried carbonizing everything from paper to bamboo to spiderwebs when
he was seeking a good light-bulb filament. Charles Goodyear messed
around in a kitchen for years, trying to convert gummy natural
rubber into a durable substance, until at last he chanced to drop
sulfurized rubber on a hot stove, performing the first crude
vulcanization.
In engineering, enlightened trial and error, not the planning of
flawless intellects, has brought most advances; this is why
engineers build prototypes. Peters and Waterman*(44) in their book
In Search of Excellence show that the same holds true of advances in
corporate products and policies. This is why excellent companies
create "an environment and a set of attitudes that encourage
experimentation," and why they evolve "in a very Darwinian way."
Factories bring order through variation and selection. Crude
quality-control systems test and discard faulty parts before
assembling products, and sophisticated quality-control systems use
statistical methods to track defects to their sources, helping
engineers change the manufacturing process to minimize defects.
Japanese engineers, building on W. Edwards Deming's work in
statistical quality control, have made such variation and selection of
industrial processes a pillar of their country's economic success.
Assembler-based systems will likewise need to measure results to
eliminate flaws.
Quality control is a sort of evolution, aiming not at change but
at eliminating harmful variations. But just as Darwinian evolution can
preserve and spread favorable mutations, so good quality control
systems can help managers and workers to preserve and spread more
effective processes, whether they appear by accident or by design.
All this tinkering by engineers and manufacturers prepares
products for their ultimate test. Out in the market, endless varieties
of wrench, car, sock, and computer compete for the favor of buyers.
When informed buyers are free to choose, products that do too little
or cost too much eventually fail to be re-produced. As in nature,
competitive testing makes yesterday's best competitor into
tomorrow's fossil. "Ecology" and "economy" share more than
linguistic roots.
Both in the marketplace and on real and imaginary battlefields,
global competition drives organizations to invent, buy, beg, and steal
ever more capable technologies. Some organizations compete chiefly
to serve people with superior goods, others compete chiefly to
intimidate them with superior weapons. The pressures of evolution
drive both.
The global technology race has been accelerating for billions of
years. The earthworm's blindness could not block the development of
sharp-eyed birds. The bird's small brain and clumsy wings could not
block the development of human hands, minds, and shotguns. Likewise,
local prohibitions cannot block advances in military and commercial
technology. It seems that we must guide the technology race or die,
yet the force of technological evolution makes a mockery of
anti-technology movements: democratic movements for local restraint
can only restrain the world's democracies, not the world as a whole.
The history of life and the potential of new technology suggest some
solutions, but this is a matter for Part Three.
-
THE EVOLUTION OF DESIGN
-
It might seem that design offers an alternative to evolution, but
design involves evolution in two distinct ways. First, design practice
itself evolves. Not only do engineers accumulate designs that work,
they accumulate design methods that work. These range from handbook
standards for choosing pipes to management systems for organizing
research and development. And as Alfred North Whitehead stated,*(45)
"The greatest invention of the nineteenth century was the invention of
the method of invention."
Second, design itself proceeds by variation and selection. Engineers
often use mathematical laws evolved to describe (for example) heat
flow and elasticity to test simulated designs before building them.
They thus evolve plans through a cycle of design, calculation,
criticism, and redesign, avoiding the expense of cutting metal. The
creation of designs thus proceeds through a nonmaterial form of
evolution.
Hooke's law, for example, describes how metal bends and stretches:
deformation is proportional to the applied stress: twice the pull,
twice the stretch. Though only roughly correct, it remains fairly
accurate until the metal's springiness finally yields to stress.
Engineers can use a form of Hooke's law to design a bar of metal
that can support a load without bending too far- and then make it just
a bit thicker to allow for inaccuracies in the law and in their design
calculations. They can also use a form of Hooke's law to describe
the bending and twisting of aircraft wings, tennis rackets, and
automobile frames. But simple mathematical equations don't wrap
smoothly around such convoluted structures. Engineers have to fit
the equations to simpler shapes (to pieces of the design), and then
assemble these partial solutions to describe the flexing of the whole.
It is a method (called "finite element analysis") that typically
requires immense calculations, and without computers it would be
impractical. With them, it has grown common.
Such simulations extend an ancient trend. We have always imagined
consequences, in hope and fear, when we have needed to select a course
of action. Simpler mental models (whether inborn or learned)
undoubtedly guide animals as well. When based on accurate mental
models, thought experiments can replace more costly (or even deadly)
physical experiments- a development evolution has favored. Engineering
simulations simply extend this ability to imagine consequences, to
make our mistakes in thought rather than deed.
In "One Highly Evolved Toolbox," J. Baldwin discusses how tools
and thought mesh in job-shop work: "You begin to build your tool
capability into the way you think about making things. As anyone who
makes a lot of stuff will tell you, the tools soon become sort of an
automatic part of the design process... But tools can't become part of
your design process if you don't know what is available and what the
various tools do."
Having a feel for tool capabilities is essential when planning a
job-shop project for delivery next Wednesday; it is equally
essential when shaping a strategy for handling the breakthroughs of
the coming decades. The better our feel for the future's tools, the
sounder will be our plans for surviving and prospering.
A craftsman in a job shop can keep tools in plain sight; working
with them every day makes them familiar to his eyes, hands, and
mind. He gets to know their abilities naturally, and can put this
knowledge to immediate creative use. But people- like us- who have
to understand the future face a greater challenge, because the
future's tools exist now only as ideas and as possibilities implicit
in natural law. These tools neither hang on the wall nor impress
themselves on the mind through sight and sound and touch- nor will
they, until they exist as hardware. In the coming years of preparation
only study, imagination, and thought*(46) can make their abilities
real to the mind.
-
WHAT ARE THE NEW REPLICATORS?
-
History shows us that hardware evolves. Test tube RNA, viruses,
and dogs all show how evolution proceeds by the modification and
testing of replicators. But hardware (today) cannot reproduce
itself- so where are the replicators behind the evolution of
technology? What are the machine genes?
Of course, we need not actually identify replicators in order to
recognize evolution. Darwin described evolution before Mendel
discovered genes, and geneticists learned much about heredity before
Watson and Crick discovered the structure of DNA. Darwin needed no
knowledge of molecular genetics to see that organisms varied and
that some left more descendants.
A replicator is a pattern that can get copies of itself made. It may
need help; without protein machines to copy it, DNA could not
replicate. But by this standard, some machines are replicators!
Companies often make machines that fall into the hands of a
competitor; the competitor then learns their secrets and builds
copies. Just as genes "use" protein machines to replicate, so such
machines "use" human minds and hands to replicate. With
nanocomputers directing assemblers and disassemblers, the
replication of hardware could even be automated.
The human mind, though, is a far subtler engine of imitation than
any mere protein machine or assembler. Voice, writing, and drawing can
transmit designs from mind to mind before they take form as
hardware. The ideas behind methods of design are subtler yet: more
abstract than hardware, they replicate and function exclusively in the
world of minds and symbol systems.
Where genes have evolved over generations and eons, mental
replicators now evolve over days and decades. Like genes, ideas split,
combine, and take multiple forms (genes can be transcribed from DNA to
RNA and back again; ideas can be translated from language to
language). Science cannot yet describe the neural patterns that embody
ideas in brains, but anyone can see that ideas mutate, replicate,
and compete. Ideas evolve.
Richard Dawkins calls*(47) bits of replicating mental patterns
"memes" (meme rhymes with cream). He says "examples of memes are
tunes, ideas, catch-phrases, clothes fashions, ways of making pots
or of building arches. Just as genes propagate themselves in the
gene pool by leaping from body to body [generation to generation]
via sperms or eggs, so memes propagate themselves in the meme pool
by leaping from brain to brain via a process which, in the broad
sense, can be called imitation."
-
THE CREATURES OF THE MIND
-
Memes replicate because people both learn and teach. They vary
because people create the new and misunderstand the old. They are
selected (in part) because people don't believe or repeat everything
they hear. As test tube RNA molecules compete for scarce copying
machines and subunits, so memes must compete for a scarce resource-
human attention and effort. Since memes shape behavior, their
success or failure is a deadly serious matter.
Since ancient times, mental models and patterns of behavior have
passed from parent to child. Meme patterns that aid survival and
reproduction have tended to spread. (Eat this root only after cooking;
don't eat those berries, their evil spirits will twist your guts.)
Year by year, people varied their actions with varying results. Year
by year, some died while others found new tricks of survival and
passed them on. Genes built brains skilled at imitation because the
patterns imitated were, on the whole, of value- their bearers, after
all, had survived to spread them.
Memes themselves, though, face their own matters of "life" and
"death": as replicators, they evolve solely to survive and spread.
Like viruses, they can replicate without aiding their host's
survival or well-being. Indeed, the meme for martyrdom-in-a-cause
can spread itself through the very act of killing its host.
Genes, like memes, survive by many strategies. Some duck genes
have spread themselves by encouraging ducks to pair off to care for
their gene-bearing eggs and young. Some duck genes have spread
themselves (when in male ducks) by encouraging rape, and some (when in
female ducks) by encouraging the planting of eggs in other ducks'
nests. Still other genes found in ducks are virus genes, able to
spread without making more ducks. Protecting eggs helps the duck
species (and the individual duck genes) survive; rape helps one set of
duck genes at the expense of others; infection helps viral genes at
the expense of duck genes in general. As Richard Dawkins points out,
genes "care" only about their own replication: they appear selfish.
But selfish motives can encourage cooperation.*(48) People seeking
money and recognition for themselves cooperate to build corporations
that serve other people's wants. Selfish genes cooperate to build
organisms that themselves often cooperate. Even so, to imagine that
genes automatically serve some greater good (-of their chromosome?-
their cell?- their body?- their species?) is to mistake a common
effect for an underlying cause. To ignore the selfishness of
replicators is to be lulled by a dangerous illusion.
Some genes in cells are out-and-out parasites. Like herpes genes
inserted in human chromosomes, they exploit cells and harm their
hosts. Yet if genes can be parasites, why not memes as well?
In The Extended Phenotype,*(49) Richard Dawkins describes a worm
that parasitizes bees and completes its life cycle in water. It gets
from bee to water by making the host bee dive to its death. Similarly,
ant brainworms must enter a sheep to complete their life cycle. To
accomplish this, they burrow into the host ant's brain, somehow
causing changes that make the ant "want" to climb to the top of a
grass stem and wait, eventually to be eaten by a sheep.
As worms enter other organisms and use them to survive and
replicate, so do memes. Indeed, the absence of memes exploiting people
for their own selfish ends would be amazing, a sign of some
powerful- indeed, nearly perfect- mental immune system. But
parasitic memes clearly do exist. Just as viruses evolve to
stimulate cells to make viruses, so rumors evolve to sound plausible
and juicy, stimulating repetition. Ask not whether a rumor is true,
ask instead how it spreads. Experience shows that ideas evolved to
be successful replicators need have little to do with the truth.
At best, chain letters, spurious rumors, fashionable lunacies, and
other mental parasites harm people by wasting their time. At worst,
they implant deadly misconceptions. These meme systems exploit human
ignorance and vulnerability. Spreading them is like having a cold
and sneezing on a friend. Though some memes act much like viruses,
infectiousness isn't necessarily bad (think of an infectious grin,
or infectious good nature). If a package of ideas has merit, then
its infectiousness simply increases its merit- and indeed, the best
ethical teachings also teach us to teach ethics. Good publications may
entertain, enrich understanding, aid judgment- and advertise gift
subscriptions. Spreading useful meme systems is like offering useful
seeds to a friend with a garden.
-
SELECTING IDEAS
-
Parasites have forced organisms to evolve immune systems, such as
the enzymes that bacteria use to cut up invading viruses, or the
roving white blood cells our bodies use to destroy bacteria. Parasitic
memes have forced minds down a similar path, evolving meme systems
that serve as mental immune systems.
The oldest and simplest mental immune system simply commands
"believe the old, reject the new." Something like this system
generally kept tribes from abandoning old, tested ways in favor of
wild new notions- such as the notion that obeying alleged ghostly
orders to destroy all the tribe's cattle and grain would somehow bring
forth a miraculous abundance of food and armies of ancestors to
drive out foreigners. (This meme package infected the Xhosa
people*(50) of southern Africa in 1856; by the next year 68,000 had
died, chiefly of starvation.)
Your body's immune system follows a similar rule: it generally
accepts all the cell types present in early life and rejects new
types, such as potential cancer cells and invading bacteria, as
foreign and dangerous. This simple reject-the-new system once worked
well, yet in this era of organ transplantation it can kill. Similarly,
in an era when science and technology regularly present facts that are
both new and trustworthy, a rigid mental immune system becomes a
dangerous handicap.
For all its shortcomings, though, the reject-the-new principle is
simple and offers real advantages. Tradition holds much that is
tried and true (or if not true, then at least workable). Change is
risky: just as most mutations are bad, so most new ideas are wrong.
Even reason can be dangerous: if a tradition links sound practices
to a fear of ghosts, then overconfident rational thought may throw out
the good with the bogus. Unfortunately, traditions evolved to be
good may have less appeal than ideas evolved to sound good- when first
questioned, the soundest tradition may be displaced by worse ideas
that better appeal to the rational mind.
Yet memes that seal the mind against new ideas protect themselves in
a suspiciously self-serving way. While protecting valuable
traditions from clumsy editing, they may also shield parasitic
claptrap from the test of truth. In times of swift change they can
make minds dangerously rigid.
Much of the history of philosophy and science may be seen as a
search for better mental immune systems, for better ways to reject the
false, the worthless, and the damaging. The best systems respect
tradition, yet encourage experiment. They suggest standards for
judging memes, helping the mind distinguish between parasites and
tools.
-
The principles of evolution provide a way to view change, whether in
molecules, organisms, technologies, minds, or cultures. The same basic
questions keep arising: What are the replicators? How do they vary?
What determines their success? How do they defend against invaders?
These questions will arise again when we consider the consequences
of the assembler revolution, and yet again when we consider how
society might deal with those consequences.
The deep-rooted principles of evolutionary change will shape the
development of nanotechnology, even as the distinction between
hardware and life begins to blur. These principles show much about
what we can and cannot hope to achieve, and they can help us focus our
efforts to shape the future. They also tell us much about what we
can and cannot foresee, because they guide the evolution not only of
hardware, but of knowledge itself.
3
Predicting and Projecting
-
The critical attitude*(51) may be described as the conscious attempt
to make our theories, our conjectures, suffer in our stead in the
struggle for the survival of the fittest. It gives us a chance to
survive the elimination of an inadequate hypothesis- when a more
dogmatic attitude would eliminate it by eliminating us.
-Sir KARL POPPER
-
AS WE LOOK FORWARD to see where the technology race leads, we should
ask three questions. What is possible, what is achievable, and what is
desirable?
First, where hardware is concerned, natural law sets limits to the
possible. Because assemblers will open a path to those limits,
understanding assemblers is a key to understanding what is possible.
Second, the principles of change and the facts of our present
situation set limits to the achievable. Because evolving replicators
will play a basic role, the principles of evolution are a key to
understanding what will be achievable.
As for what is desirable or undesirable, our differing dreams spur a
quest for a future with room for diversity, while our shared fears
spur a quest for a future of safety.
These three question- of the possible, the achievable, and the
desirable- frame an approach to foresight. First, scientific and
engineering knowledge form a map of the limits of the possible. Though
still blurred and incomplete, this map outlines the permanent limits
within which the future must move. Second, evolutionary principles
determine what paths lie open, and set limits to achievement-
including lower limits, because advances that promise to improve
life or to further military power will be virtually unstoppable.
This allows a limited prediction: If the eons-old evolutionary race
does not somehow screech to a halt, then competitive pressures will
mold our technological future to the contours of the limits of the
possible. Finally, within the broad confines of the possible and the
achievable, we can try to reach a future we find desirable.
-
PITFALLS OF PROPHECY
-
But how can anyone predict the future? Political and economic trends
are notoriously fickle, and sheer chance rolls dice across continents.
Even the comparatively steady advance of technology often eludes
prediction.
Prognosticators often guess at the times and costs required to
harness new technologies. When they reach beyond outlining
possibilities and attempt accurate predictions, they generally fail.
For example, though the space shuttle was clearly possible,
predictions of its cost and initial launch date were wrong by
several years and billions of dollars. Engineers cannot accurately
predict when a technology will be developed, because development
always involves uncertainties.
But we have to try to predict and guide development. Will we develop
monster technologies before cage technologies, or after? Some
monsters, once loosed, cannot be caged. To survive, we must keep
control by speeding some developments and slowing others.
Though one technology can sometimes block the dangers of another
(defense vs. offense, pollution controls vs. pollution), competing
technologies often go in the same direction. On December 29, 1959,
Richard Feynman (now a Nobel laureate) gave a talk*(52) at an annual
meeting of the American Physical Society entitled "There's Plenty of
Room at the Bottom." He described a non-biochemical approach to
nanomachinery (working down, step by step, using larger machines to
build smaller machines), and stated that the principles of physics "do
not speak against the possibility of maneuvering things atom by
atom. It is not an attempt to violate any laws; it is something, in
principle, that can be done; but, in practice, it has not been done
because we are too big.... Ultimately, we can do chemical
synthesis.... put the atoms down where the chemist says, and so you
make the substance." In brief, he sketched another, nonbiochemical
path to the assembler. He also stated, even then, that it is "a
development which I think cannot be avoided."
As I will discuss in Chapters 4 and 5, assemblers and intelligent
machines will simplify many questions regarding the time and cost of
technological developments. But questions of time and cost will
still muddy our view of the period between the present and these
breakthroughs. Richard Feynman saw in 1959 that nanomachines could
direct chemical synthesis, presumably including the synthesis of
DNA. Yet he could foresee neither the time nor the cost of doing so.
In fact, of course, biochemists developed techniques for making
DNA without programmable nanomachines, using shortcuts based on
specific chemical tricks. Winning technologies often succeed because
of unobvious tricks and details. In the mid-1950s physicists could see
that basic semiconductor principles made microcircuits physically
possible, but foreseeing how they would be made- foreseeing the
details of mask-making, resists, oxide growth, ion implantation,
etching, and so forth, in all their complexity- would have been
impossible. The nuances of detail and competitive advantage that
select winning technologies make the technology race complex and its
path unpredictable.
But does this make long-term forecasting futile? In a race toward
the limits set by natural law, the finish line is predictable even
if the path and the pace of the runners are not. Not human whims but
the unchanging laws of nature draw the line between what is physically
possible and what is not- no political act, no social movement can
change the law of gravity one whit. So however futuristic they may
seem, sound projections of technological possibilities are quite
distinct from predictions. They rest on timeless laws of nature, not
on the vagaries of events.
It is unfortunate that this insight remains rare. Without it, we
stumble in a daze across the landscape of the possible, confusing
mountains with mirages and discounting both. We look ahead with
minds and cultures rooted in the ideas of more sluggish times, when
both science and technological competition lacked their present
strength and speed. We have only recently begun to evolve a
tradition of technological foresight.
-
SCIENCE AND NATURAL LAW
-
Science and technology intertwine. Engineers use knowledge
produced by scientists; scientists use tools produced by engineers.
Scientists and engineers both work with mathematical descriptions of
natural laws and test ideas with experiments. But science and
technology differ radically in their basis, methods, and aims.
Understanding these differences is crucial to sound foresight.
Though both fields consist of evolving meme systems, they evolve under
different pressures. Consider the roots of scientific knowledge.
Through most of history, people had little understanding of
evolution. This left philosophers thinking that sensory evidence,
through reason, must somehow imprint on the mind all human
knowledge- including knowledge of natural law. But in 1737, the
Scottish philosopher David Hume presented them with a nasty puzzle: he
showed that observations cannot logically prove a general rule, that
the Sun shining day after day proves nothing, logically, about its
shining tomorrow. And indeed, someday the Sun will fail, disproving
any such logic. Hume's problem appeared to destroy the idea of
rational knowledge, greatly upsetting rational philosophers (including
himself). They thrashed and sweated, and irrationalism gained
ground. In 1945, philosopher Bertrand Russell observed*(53) that
"the growth of unreason throughout the nineteenth century and what has
passed of the twentieth is a natural sequel to Hume's destruction of
empiricism." Hume's problem-meme had undercut the very idea of
rational knowledge, at least as people had imagined it.
In recent decades, Karl Popper (perhaps the scientists' favorite
philosopher of science), Thomas Kuhn, and others have recognized
science as an evolutionary process. They see it not as a mechanical
process by which observations somehow generate conclusions, but as a
battle where ideas compete for acceptance.
All ideas, as memes, compete for acceptance, but the meme system
of science is special: it has a tradition of deliberate idea mutation,
and a unique immune system for controlling the mutants. The results of
evolution vary with the selective pressures applied, whether among
test tube RNA molecules, insects, ideas, or machines. Hardware evolved
for refrigeration differs from hardware evolved for transportation,
hence refrigerators make very poor cars. In general, replicators
evolved for A differ from those evolved for B. Memes are no exception.
Broadly speaking, ideas can evolve to seem true or they can evolve
to be true*(54) (by seeming true to people who check ideas carefully).
Anthropologists and historians have described what happens when
ideas evolve to seem true among people lacking the methods of science;
the results (the evil-spirit theory of disease, the lights-on-a-dome
theory of stars, and so forth) were fairly consistent worldwide.
Psychologists probing people's naive misconceptions about how
objects fall have found beliefs like those that evolved into formal
"scientific" systems during the Middle Ages, before the work of
Galileo and Newton.
Galileo and Newton used experiments and observations to test ideas
about objects and motion, beginning an era of dramatic scientific
progress: Newton evolved a theory that survived every test then
available. Their method of deliberate testing killed off ideas that
strayed too far from the truth, including ideas that had evolved to
appeal to the naive human mind.
This trend has continued. Further variation and testing have
forced the further evolution of scientific ideas, yielding some as
bizarre-seeming as the varying time and curved space of relativity, or
the probabilistic particle wave functions of quantum mechanics. Even
biology has discarded the special life-force expected by early
biologists, revealing instead elaborate systems of invisibly small
molecular machines. Ideas evolved to be true (or close to the truth)
have again and again turned out to seem false- or incomprehensible.
The true and the true-seeming have turned out to be as different as
cars and refrigerators.
Ideas in the physical sciences have evolved under several basic
selection rules. First, scientists ignore ideas that lack testable
consequences; they thus keep their heads from being clogged by useless
parasites. Second, scientists seek replacements for ideas that have
failed tests. Finally, scientists seek ideas that make the widest
possible range of exact predictions. The law of gravity, for
example, describes how stones fall, planets orbit, and galaxies swirl,
and makes exact predictions that leave it wide open to disproof. Its
breadth and precision likewise give it broad usefulness, helping
engineers both to design bridges and to plan spaceflights.
The scientific community provides an environment where such memes
spread, forced by competition and testing to evolve toward power and
accuracy. Agreement on the importance of testing theories holds the
scientific community together through fierce controversies over the
theories themselves.
Inexact, limited evidence can never prove an exact, general theory
(as Hume showed), but it can disprove some theories and so help
scientists choose among them. Like other evolutionary processes,
science creates something positive (a growing store of useful
theories) through a double negative (disproof of incorrect
theories). The central role of negative evidence accounts for some
of the mental upset caused by science: as an engine of disproof, it
can uproot cherished beliefs, leaving psychological voids that it need
not refill.
In practical terms, of course, much scientific knowledge is as solid
as a rock dropped on your toe. We know Earth circles the Sun (though
our senses suggest otherwise) because the theory fits endless
observations, and because we know why our senses are fooled. We have
more than a mere theory that atoms exist: we have bonded them to
form molecules, tickled light from them, seen them under microscopes
(barely), and smashed them to pieces. We have more than a mere
theory of evolution: we have observed mutations, observed selection,
and observed evolution in the laboratory. We have found the traces
of past evolution in our planet's rocks, and have observed evolution
shaping our tools, our minds, and the ideas in our minds- including
the idea of evolution itself. The process of science has hammered
out a unified explanation of many facts, including how people and
science themselves came to be.
When science finishes disproving theories, the survivors often
huddle so close together*(55) that the gap between them makes no
practical difference. After all, a practical difference between two
surviving theories could be tested and used to disprove one of them.
The differences among modern theories of gravity, for instance, are
far too subtle to trouble engineers who are planning flights through
the gravity fields of space. In fact, engineers plan spaceflights
using Newton's disproved theory because it is simpler than Einstein's,
and is accurate enough. Einstein's theory of gravity has survived
all tests so far, yet there is no absolute proof for it and there
never will be. His theory makes exact predictions about everything
everywhere (at least about gravitational matters), but scientists
can only make approximate measurements of some things somewhere.
And, as Karl Popper points out,*(56) one can always invent a theory so
similar to another that existing evidence cannot tell them apart.
Though media debates highlight the shaky, disputed borders of
knowledge, the power of science to build agreement remains clear.
Where else has agreement on so much grown so steadily and so
internationally? Surely not in politics, religion, or art. Indeed, the
chief rival of science is a relative: engineering, which also
evolves through proposals and rigorous testing.
-
SCIENCE VS. TECHNOLOGY
-
As IBM Director of Research Ralph E. Gomory says,*(57) "The
evolution of technology development is often confused with science
in the public mind." This confusion muddles our efforts at foresight.
Though engineers often tread uncertain ground, they are not doomed
to do so, as scientists are. They can escape the inherent risks of
proposing precise, universal scientific theories. Engineers need
only show that under particular conditions particular objects will
perform well enou |
