Introduction
모든 사람은 지혜와 부를 원한다. 그러나 우리의 건강은 그것들을 얻기전에 소진해 버린다. 우리의 생을 연장하고 마음을 증진시키기 위해 미래에는 우리의 몸과 두뇌를 변화시킬 필요가 있을 것이다. 그를 위해 우리는 먼저 다윈의 진화론이 우리에게 가져다 준 것이 얼마나 소중한 것이었는지를 고려해야만 한다. 그리고나서 우리는 낡아빠진 신체부위의 교체를 통해서 건강을 잃는 대부분의 문제를 해결할 것이라는 상상을 할 수 있다. 우리는 그를 위해 우리의 뇌를 증진시키고 더 많은 지혜를 얻기위한 전략을 발명해 내야한다. 궁극적으로 우리는 nanotechnology 를 사용하여 우리의 뇌를 완전히 교체할 것이다. 일단 생물의 한계로부터 해방되어 우리는 우리 생의 길이를 결정할수 있을 것이고 -불멸의 조건하에서- 그외의 상상할수 없는 능력들을 선택할수 있을 것이다.
그러한 미래에 부를 얻는것은 문제가 되지 않으며 문제는 그것을 조절하는 것일것이다. 분명히 그러한 변화는 상상하기가 어려우며 많은 연구자들은 이러한 진보가 불가능하다고 주장하는데 특히 인공지능의 영역에서 그러하다. 그러나 이러한 전이를 가능하게 하기위해 필요한 과학들은 이미 이루기 시작하였고 이러한 새로운 세계가 어떻게 될 것인지를 고려할 때가 온 것이다.
Everyone wants wisdom and wealth. Nevertheless, our health often gives out
before we achieve them. To lengthen our lives, and improve our minds, in the
future we will need to change our our bodies and brains. To that end, we first
must consider how normal Darwinian evolution brought us to where we are. Then
we must imagine ways in which future replacements for worn body parts might
solve most problems of failing health. We must then invent strategies to augment
our brains and gain greater wisdom. Eventually we will entirely replace our
brains -- using nanotechnology. Once delivered from the limitations of biology,
we will be able to decide the length of our lives--with the option of immortality--
and choose among other, unimagined capabilities as well.
In such a future, attaining wealth will not be a problem; the trouble will
be in controlling it. Obviously, such changes are difficult to envision, and
many thinkers still argue that these advances are impossible--particularly in
the domain of artificial intelligence. But the sciences needed to enact this
transition are already in the making, and it is time to consider what this new
world will be like.
Health and Longevity.
Such a future cannot be realized through biology. In recent times we've learned a lot about health and how to maintain it. We have devised thousands of specific treatments for particular diseases and disabilities. However, we do not seem to have increased the maximum length of our life span. Franklin lived for 84 years and, except in popular legends and myths, no one has ever lived twice that long. According to the estimates of Roy Walford, professor of pathology at UCLA Medical School, the average human life span was about 22 years in ancient Rome; about 50 in the developed countries in 1900, and today stands at about 75. Still, each of those curves seems to terminate sharply near 115 years. Centuries of improvements in health care have had no effect on that maximum.
Why are our life spans so limited? The answer is simple: Natural selection
favors the genes of those with the most descendants. Those numbers tend to grow
exponentially with the number of generations--and so this favors the genes of
those who reproduce at earlier ages. Evolution does not usually favor genes
that lengthen lives beyond that amount adults need to care for their young.
Indeed, it may even favor offspring who do not have to compete with living parents.
Such competition could promote the accumulation of genes that cause death.
For example, after spawning, the Mediterranean octopus (O. Hummelincki) promptly
stops eating and starves to death. If we remove a certain gland though, the
octopus continues to eat, and lives twice as long. Many other animals are programmed
to die soon after they cease reproducing. Exceptions to this include those long-lived
animals, like ourselves and the elephants, whose progeny learn so much from
the social transmission of accumulated knowledge.
We humans appear to be the longest lived warm-blooded animals. What selective
pressure might have led to our present longevity which is almost twice that
of our other primate relatives? This is related to wisdom! Among all mammals,
our infants are the most poorly equipped to survive by themselves. Perhaps we
needed not only parents, but grandparents too, to care for us and to pass on
precious survival tips.
Even with such advice, there are many causes of mortality to which we might
succumb. Some deaths result from infections. Our immune systems have evolved
versatile ways to deal with most such diseases. Unhappily though, those very
same immune systems often injure us by treating various parts of ourselves as
though they, too, were infectious invaders. This blindness leads to diseases
such as diabetes, multiple sclerosis, rheumatoid arthritis, and many others.
We are also subject to injuries that our bodies cannot repair. Namely, accidents,
dietary imbalances, chemical poisons, heat, radiation, and sundry other influences
can deform or chemically alter the molecules inside our cells so that they are
unable to function. Some of these errors get corrected by replacing defective
molecules. However, when the replacement rate is too slow, errors accumulate.
For example, when the proteins of the eyes' lenses lose their elasticity, we
lose our ability to focus and need bifocal spectacles--one of Franklin's inventions.
The major causes of death result from the effects of inherited genes. These
genes include those that seem to be largely responsible for heart disease and
cancer, the two largest causes of mortality, as well as countless other disorders
such as cystic fibrosis and sickle cell anemia. New technologies should be able
to prevent some of these disorders by finding ways to replace those genes.
Perhaps worst of all, we suffer from defects inherent in how our genetic
system works. The relationship between genes and cells is exceedingly indirect;
there are no blueprints or maps to guide our genes as they build or rebuild
the body. As we learn more about our genes, we will hopefully be able to correct,
or at least postpone many conditions that still plague our later years.
Most likely, eventual senescence is inevitable in all biological organisms.
To be sure, certain species (including some varieties of fish, tortoises, and
lobsters) do not appear to show any systematic increase of mortality rate with
age. These animals seem to die mainly from external causes, such as predators
or a lack of food. Still, we have no records of animals that have lived for
as long as 200 years-- although this does not prove that none exist. Walford
and many others believe that a carefully designed diet, one seriously restricted
in calories, can significantly increase a human’s life span--but cannot prevent
our ultimate death.
Biological Wearing-Out.
As we learn more about our genes, we will hopefully be able to correct, or
at least postpone many conditions that still plague our later years. However,
even if we found cures for each specific disease, we would still have to deal
with the general problem of "wearing out." The normal function of
every cell involves thousands of chemical processes, each of which sometimes
makes random mistakes. Our bodies use many kinds of correction techniques, each
triggered by a specific type of mistake. However, those random errors happen
in so many different ways that no low-level scheme can correct them all.
The problem is that our genetic systems were not designed for very long-term
maintainance. The relationship between genes and cells is exceedingly indirect;
there are no blueprints or maps to guide our genes as they build or rebuild
the body. To repair defects on larger scales, a body would need some sort of
catalogue that specified which types of cells should be located where. In computer
programs it is easy to install such redundancy. Many computers maintain unused
copies of their most critical "system" programs, and routinely check
their integrity. However, no animals have evolved like schemes, presumably because
such algorithms cannot develop through natural selection. The trouble is that
error correction then would stop mutation--which would ultimately slow the rate
of evolution of an animal's descendants so much that they would be unable to
adapt to changes in their environments.
Could we live for several centuries simply by changing some number of genes?
After all, we now differ from our evolutionary relatives, the gorillas and chimpanzees,
by only a few thousand genes--and yet we live almost twice as long. If we assume
that only a small fraction of those new genes caused that increase in life span,
then perhaps no more than a hundred or so of those genes were involved. Still,
even if this turned out to be true, it would not guarantee that we could gain
another century by changing another hundred genes. We might need to change only
a few of them--or we might have to change a good many more.
Making new genes and installing them is slowly becoming feasible. But we
are already exploiting another approach to combat biological wear and tear:
replacing each organ that threatens to fail with a biological or artificial
substitute. Some replacements are already routine. Others are on the horizon.
Hearts are merely clever pumps. Muscles and bones are motors and beams. Digestive
systems are chemical reactors. Eventually, we will solve the problems associated
with transplanting or replacing all of these parts.
When we consider replacing a brain though, a transplant will not work. You
cannot simply exchange your brain for another and remain the same person. You
would lose the knowledge and the processes that constitute your identity. Nevertheless,
we might be able to replace certain worn out parts of brains by transplanting
tissue-cultured fetal cells. This procedure would not restore lost knowledge
--but that might not matter as much as it seems. We probably store each fragment
of knowledge in several different places, in different forms. New parts of the
brain could be retrained and reintegrated with the rest -- and some of that
might even happen spontaneously.
Limitations of Human Wisdom.
Even before our bodies wear out. I suspect that we run into limitations of
our brains. As a species we seem to have reached a plateau in our intellectual
development. There's no sign that we're getting smarter. Was Albert Einstein
a better scientist than Newton or Archimedes? Has any playwright in recent years
topped Shakespeare or Euripides? We have learned a lot in two thousand years,
yet much ancient wisdom still seems sound--which makes me suspect that we haven't
been making much progress. We still don't know how to deal with conflicts between
individual goals and global interests. We are so bad at making important decisions
that, whenever we can, we leave to chance what we are unsure about.
Why is our wisdom so limited? Is it because we do not have the time to learn
very much, or that we lack enough capacity? Is it because, as in popular legend,
we use only a fraction of our brains? Could better education help? Of course,
but only to a point. Even our best prodigies learn no more than twice as quickly
as the rest. Everything takes us too long to learn because our brains are so
terribly slow. It would certainly help to have more time, but longevity is not
enough. The brain, like other finite things, must reach some limits to what
it can learn. We don't know what those limits are; perhaps our brains could
keep learning for several more centuries. Ultimately, though, we will need to
increase their capacity.
The more we learn about our brains, the more ways we will find to improve
them. Each brain has hundreds of specialized regions. We know only a little
about what each one does -- but as soon as we find out how any one part works,
researchers will try to devise ways to extend that organ's capacity. They will
also conceive of entirely new abilities that biology has never provided. As
these inventions accumulate, we'll try to connect them to our brains -- perhaps
through millions of microscopic electrodes inserted into the great nerve-bundle
called the corpus callosum, the largest data-bus in the brain. With further
advances, no part of the brain will be out of bounds for attaching new accessories.
In the end, we will find ways to replace every part of the body and brain--and
thus repair all the defects and flaws that make our lives so brief.
Needless to say, in doing so, we'll be making ourselves into machines.
Does this mean that machines will replace us? I don't feel that it makes
much sense to think in terms of "us" and "them." I much
prefer the attitude of Hans Moravec of Carnegie-Mellon University, who suggests
that we think of those future intelligent machines as our own "mind- children."
In the past, we have tended to see ourselves as a final product of evolution
-- but our evolution has not ceased. Indeed, we are now evolving more rapidly--although
not in the familiar, slow Darwinian way. It is time that we started to think
about our new emerging identities. We now can design systems based on new kinds
of "unnatural selection" that can exploit explicit plans and goals,
and can also exploit the inheritance of acquired characteristics. It took a
century for evolutionists to train themselves to avoid such ideas--biologists
call them 'teleological' and Lamarckian'- -but now we may have to change those
rules!
Replacing the brain
Almost all the knowledge that we learn is embodied in various networks inside
our brains. These networks consist of huge numbers of tiny nerve cells, and
even larger numbers of smaller structures called synapses, which control how
signals jump from one nerve cell to another. To make a replacement of your brain,
we would need to know something about how each of your synapses relates to the
two cells it bridges. We would also have to know how each of those structures
responds to the various electric fields, hormones, neurotransmitters, nutrients
and other chemicals that are active in its neighborhood. Your brain contains
trillions of synapses, so this is no small requirement.
Fortunately, we would not need to know every minute detail. If that were
so, our brains wouldn't work in the first place. In biological organisms, generally
each system has evolved to be insensitive to most details of what goes on in
the smaller subsystems on which it depends. Therefore, to copy a functional
brain, it should suffice to replicate just enough of the function of each part
to produce its important effects on other parts.
Suppose that we wanted to copy a machine, such as a brain, that contained
a trillion components. Today we could not do such a thing (even were we equipped
with the necessary knowledge) if we had to build each component separately.
However, if we had a million construction machines that could each build a thousand
parts per second, our task would take only minutes. In the decades to come,
new fabrication machines will make this possible. Most present-day manufacturing
is based on shaping bulk materials. In contrast, the field called 'nanotechnology'
aims to build materials and machinery by placing each atom and molecule precisely
where we want it.
By such methods, we could make truly identical parts--and thus escape from
the randomness that hinders conventionally made machines. Today, for example,
when we try to etch very small circuits, the sizes of the wires vary so much
that we cannot predict their electrical properties. However, if we can locate
each atom exactly, then those wires will be indistinguishable. This would lead
to new kinds of materials that current techniques could never make; we could
endow them with enormous strength, or novel quantum properties. These products
in turn will lead to computers as small as synapses, having unparalleled speed
and efficiency.
Once we can use these techniques to construct a general-purpose assembly
machine that operates on atomic scales, further progress should be swift. If
it took one week for such a machine to make a copy of itself, then we could
have a billion copies in less than a year.
These devices would transform our world. For example, we could program them
to fabricate efficient solar energy collecting devices and apply these to nearby
surfaces, so that they could power themselves. In this way, we could grow fields
of micro-factories in much the same way that we now grow trees. In such a future,
we will have little trouble attaining wealth, but rather in learning how to
control it. In particular, we must always take care when dealing with things
(such as ourselves) that might be able to reproduce themselves.
Limits of Human Memory.
If we want to consider augmenting our brains, we might first ask how much
a person knows today. Thomas K. Landauer of Bell Communications Research reviewed
many experiments in which people were asked to read text, look at pictures,
and listen to words, sentences, short passages of music, and nonsense syllables.
They were later tested in various ways to see how much they remembered. In none
of these situations were people able to learn, and later remember, more than
about 2 bits per second, for any extended period. If you could maintain that
rate for twelve hours every day for 100 years, the total would be about three
billion bits -- less than what we can store today on a regular 5-inch Compact
Disk. In a decade or so, that amount should fit on a single computer chip.
Although these experiments do not much resemble what we do in real life,
we do not have any hard evidence that people can learn more quickly. Despite
those popular legends about people with 'photographic memories,' no one seems
to have mastered, word for word, the contents of as few as one hundred books--or
of a single major encyclopedia. The complete works of Shakespeare come to about
130 million bits. Landauer's limit implies that a person would need at least
four years to memorize them. We have no well-founded estimates of how much information
we require to perform skills such as painting or skiing, but I don't see any
reason why these activities shouldn't be similarly limited.
The brain is believed to contain the order of a hundred trillion synapses--which
should leave plenty of room for those few billion bits of reproducible memories.
Someday though it should be feasible to build that much storage space into a
package as small as a pea, using nanotechnology.
The Future of Intelligence.
Once we know what we need to do, our nanotechnologies should enable us to
construct replacement bodies and brains that won't be constrained to work at
the crawling pace of "real time." The events in our computer chips
already happen millions of times faster than those in brain cells. Hence, we
could design our "mind-children" to think a million times faster than
we do. To such a being, half a minute might seem as long as one of our years,
and each hour as long as an entire human lifetime.
But could such beings really exist? Many thinkers firmly maintain that machines
will never have thoughts like ours, because no matter how we build them, they'll
always lack some vital ingredient. They call this essence by various names--like
sentience, consciousness, spirit, or soul. Philosophers write entire books to
prove that, because of this deficiency, machines can never feel or understand
the sorts of things that people do. However, every proof in each of those books
is flawed by assuming, in one way or another, the thing that it purports to
prove--the existence of some magical spark that has no detectable properties.
I have no patience with such arguments. We should not be searching for any
single missing part. Human thought has many ingredients, and every machine that
we have ever built is missing dozens or hundreds of them! Compare what computers
do today with what we call "thinking." Clearly, human thinking is
far more flexible, resourceful, and adaptable. When anything goes even slightly
wrong within a present-day computer program, the machine will either come to
a halt or produce some wrong or worthless results. When a person thinks, things
constantly going wrong as well--yet this rarely thwarts us. Instead, we simply
try something else. We look at our problem a different way, and switch to another
strategy. The human mind works in diverse ways. What empowers us to do this?
On my desk lies a textbook about the brain. Its index has about 6000 lines
that refer to hundreds of specialized structures. If you happen to injure some
of these, you could lose your ability to remember the names of animals. Another
injury might leave you unable to make any long range plans. Yet another kind
of impairment could render you prone to suddenly utter dirty words, because
of damage to the machinery that normally censors that sort of expression. We
know from thousands of similar facts that the brain contains diverse machinery.
Thus, your knowledge is represented in various forms that are stored in different
regions of the brain, to be used by different processes. What are those representations
like? In the brain, we do not yet know. However, in the field of Artificial
Intelligence, researchers have found several useful ways to represent knowledge,
each better suited to some purposes than to others. The most popular ones use
collections of "If-Then" rules. Other systems use structures called
'frames'--which resemble forms that are filled out. Yet other programs use web-
like networks, or schemes that resemble tree-like scripts. Some systems store
knowledge in language- like sentences, or in expressions of mathematical logic.
A programmer starts any new job by trying to decide which representation will
best accomplish the task at hand. Typically then, a computer program uses only
a single representation and if this should fail, the system breaks down. This
shortcoming justifies the common complaint that computers don't really "understand"
what they're doing.
But what does it mean to understand? Many philosophers have declared that
understanding (or meaning, or consciousness) must be a basic, elemental ability
that only a living mind can possess. To me, this claim appears to be a symptom
of "physics envy"--that is, they are jealous of how well physical
science has explained so much in terms of so few principles. Physicists have
done very well by rejecting all explanations that seem too complicated, and
searching, instead, for simple ones. However, this method does not work when
we're dealing with the full complexity of the brain. Here is an abridgment of
what I said about understanding in my book, The Society of Mind.
"If you understand something in only one way, then you don't really understand
it at all. This is because, if something goes wrong, you get stuck with a thought
that just sits in your mind with nowhere to go. The secret of what anything
means to us depends on how we've connected it to all the other things we know.
This is why, when someone learns 'by rote,' we say that they don't really understand.
However, if you have several different representations then, when one approach
fails you can try another. Of course, making too many indiscriminate connections
will turn a mind to mush. But well-connected representations let you turn ideas
around in your mind, to envision things from many perspectives until you find
one that works for you. And that's what we mean by thinking!"
I think that this flexibility explains why thinking is easy for us and hard
for computers, at the moment. In The Society of Mind, I suggest
that the brain rarely uses only a single representation. Instead, it always
runs several scenarios in parallel so that multiple viewpoints are always available.
Furthermore, each system is supervised by other, higher-level ones that keep
track of their performance, and reformulate problems when necessary. Since each
part and process in the brain may have deficiencies, we should expect to find
other parts that try to detect and correct such bugs.
In order to think effectively, you need multiple processes to help you describe,
predict, explain, abstract, and plan what your mind should do next. The reason
we can think so well is not because we house mysterious spark-like talents and
gifts, but because we employ societies of agencies that work in concert to keep
us from getting stuck. When we discover how these societies work, we can put
them to inside computers too. Then if one procedure in a program gets stuck,
another might suggest an alternative approach. If you saw a machine do things
like that, you'd certainly think it was conscious.
The Failures of Ethics
This article bears on our rights to have children, to change our genes, and
to die if we so wish. No popular ethical system yet, be it humanist or religion-based,
has shown itself able to face the challenges that already confront us. How many
people should occupy Earth? What sorts of people should they be? How should
we share the available space? Clearly, we must change our ideas about making
additional children. Individuals now are conceived by chance. Someday, though,
they could be 'composed' in accord with considered desires and designs. Furthermore,
when we build new brains, these need not start out the way ours do, with so
little knowledge about the world. What sorts of things should our mind-children
know? How many of them should we produce- -and who should decide their attributes?
Traditional systems of ethical thought are focused mainly on individuals,
as though they were the only things of value. Obviously, we must also consider
the rights and the roles of larger scale beings--such as the super-persons we
call cultures, and the the great, growing systems called sciences, that help
us to understand other things. How many such entities do we want? Which are
the kinds that we most need? We ought to be wary of ones that get locked into
forms that resist all further growth. Some future options have never been seen:
Imagine a scheme that could review both your and my mentalities, and then compile
a new, merged mind based upon that shared experience.
Whatever the unknown future may bring, already we're changing the rules that
made us. Although most of us will be fearful of change, others will surely want
to escape from our present limitations. When I decided to write this article,
I tried these ideas out on several groups and had them respond to informal polls.
I was amazed to find that at least three quarters of the audience seemed to
feel that our life spans were already too long. "Why would anyone want
to live for five hundred years? Wouldn't it be boring? What if you outlived
all your friends? What would you do with all that time?" they asked. It
seemed as though they secretly feared that they did not deserve to live so long.
I find it rather worrisome that so many people are resigned to die. Might not
such people be dangerous, who feel that they do not have much to lose?
My scientist friends showed few such concerns. "There are countless
things that I want to find out, and so many problems I want to solve, that I
could use many centuries," they said. Certainly, immortality would seem
unattractive if it meant endless infirmity, debility, and dependency upon others--but
we're assuming a state of perfect health. Some people expressed a sounder concern--that
the old ones must die because young ones are needed to weed out their worn-out
ideas. However, if it's true, as I fear, that we are approaching our intellectual
limits, then that response is not a good answer. We'd still be cut off from
the larger ideas in those oceans of wisdom beyond our grasp.
Will robots inherit the earth? Yes, but they will be our children. We owe
our minds to the deaths and lives of all the creatures that were ever engaged
in the struggle called Evolution. Our job is to see that all this work shall
not end up in meaningless waste.
Further Reading
Longevity, Senescence, and the Genome, Caleb E. Finch; Univ of Chicago Press, 1994
MAXIMUM LIFE SPAN.1983. Roy L. Walford. W. W. Norton and Company,
THE SOCIETY OF MIND, Marvin Minsky. Simon and Schuster,
MIND CHILDREN Hans Moravec, Harvard University Press, 1988.
NANOSYSTEMS, K. Eric Drexler. John Wiley & Sons, 1992.
THE TURING OPTION, Marvin Minsky and Harry Harrison. Warner Books, 1992.
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