PART ix
"Postscript"
Let us review a few of the fundamental issues underlying the age of
intelligent machines.
Will machines reach human levels of intelligence?
As I noted in the last section of the previous chapter, the strengths of
today's machine intelligence are quite different from those of human intelligence and in
many ways complement it. Once we have defined the transformations and methods underlying
intelligent processes, a computer can carry them out tirelessly and at great speed. It can
call upon a huge and extremely reliable memory and keep track of billions of facts and
their relationships. Human intelligence, on the other hand, though weak at mastering
facts, still excels at turning information into knowledge. The ability to recognize,
understand and manipulate the subtle networks of abstraction inherent in knowledge
continues to set human intelligence apart.
Yet computers are clearly advancing in these skills. Within narrow
domains - diagnosing certain classes of diseases, performing financial judgements, and
many other specialized tasks - computers already rival human experts. During the 1980s
expert systems went from research experiments to commercially viable tools that are relied
upon daily to perform important jobs. Computers have also begun in recent years to master
the pattern-recognition tasks inherent in vision and hearing. Though not yet up to human
standards, pattern recognition technology is sufficiently advanced to perform a wide
variety of practical tasks. It is difficult to estimate when these capabilities will reach
human levels, but there does not appear to be any fundamental barrier to achieving such
levels. Undoubtedly, computers will achieve such levels gradually; no bell will ring when
it happens.
What is clear is that by the time computers achieve human levels of
performance in those areas of traditional human strength, they will also have greatly
enhanced their areas of traditional superiority. (Not all experts agree with this. Doug
Hofstadter, for example, speculates in Godel, Escher, Bach that a future "actually
intelligent" machine may not be able to do fast accurate arithmetic, because it will
get distracted and confused by the concepts triggered by the numbers - a dubious
proposition in my view). Once a computer can read and understand what it is reading, there
is no reason why it should not read everything ever written (encyclopedias, reference
works, books, journals and magazines, data bases, etc.) and thus master all knowledge. As
Norbert Wiener has pointed out, no human being has had a complete mastery of human
knowledge for the past couple centuries (and it is doubtful in my view that anyone has
ever had such mastery). Even mere human levels of intelligence combined with a thorough
mastery of all knowledge would give computers unique intellectual skills. Combine these
attributes with computers' traditional strengths of speed, tireless operation, prodigious
and unfailing memory, and extremely rapid communication, and the result will be
formidable. We are, of course, not yet on the threshold of this vision. This early phase
of the age of intelligent machines is providing us with obedient servants that are not yet
intelligent enough to question our demands of them.
Minsky points out that we have trouble imagining machines achieving the
capabilities we have because of a deficiency in our concept of a machine. The human race
first encountered machines (of its own creation) as devices with a few dozen, and in some
cases a few hundred, active parts. Today, our computerized machines have millions of
active components, yet our concept of a machine as a relatively inflexible device with
only a handful of behavioral options has not changed. By the end of this century chips
with over a billion components are anticipated, and we will enter an era of machines with
many billions of components. Clearly, the subtleness and intelligence of the behavior of
machines at those different levels of complexity are quite different. Emulating human
levels of performance will require trillions, perhaps thousands of trillions, of
components. At current rates of progress, we shall achieve such levels of complexity early
in the next century. Human-level intellig! ence will not automatically follow, but
reasonable extrapolations of the rate of progress of machine intelligence in a broad
variety of skills in pattern recognition, fine motor coordination, decision making, and
knowledge acquisition leads to the conclusion that there is no fundamental barrier to the
AI field's ultimately achieving this objective.
Can a machine think?
The question sounds innocuous enough, but our approach to it rests on
the meanings we ascribe to the terms "machine" and "think." Consider
first the question of whether or not a human being is a machine. A human being is
certainly not like the early human-made machines, with only a handful of parts. Yet are we
fundamentally different from a machine, one with, say, a few trillion parts? After all,
our bodies and brains are presumably subject to the same natural laws as our machines. As
I stated earlier, this is not an easy question, and several thousand years of
philosophical debate have failed to answer it. If we assume that the answer to this
question is no (humans are not fundamentally different from machines), then we have
answered the original question. We presumably think, and if indeed we are machines, then
we must conclude that machines can think. If, on the other hand, we assume that we are in
some way fundamentally different from a machine, then our answer depends on our definition
of the word "think."
First, let us assume a behavioral definition, that is, a definition of
thinking based on outwardly observable behavior. Under this definition, a machine should
be considered to think if it appears to engage in intelligent behavior. This,
incidentally, appears to be the definition used by the children I interviewed (see the
section "Naive Experts" in Chapter 2). Now the answer is simply a matter of the
level of performance we expect. If we accept levels of performance in specific areas that
would be considered intelligent if performed by human beings, then we have achieved
intelligent behavior in our machines already, and thus we can conclude (as did the
children I talked with) that today's computers are thinking. If, on the other hand, we
expect an overall level of cognitive ability comparable to the full range of human
intelligence, then today's computers cannot be regarded as thinking. If one accepts my
conclusion above that computers will eventually achieve human levels of intellectual
ability, then we can conclude that it is inherently possible for a machine to think, but
that machines on earth have not yet started to do so.
If one accepts instead an intuitive definition of thinking, that is, an
entity is considered to be thinking if it "seems" to be thinking, then responses
will vary widely with the person assessing the "seeming." The children I spoke
to felt that computers seemed to think, but many adults would disagree. For myself, I
would say that computers do not yet seem to be thinking most of the time, although
occasionally a clever leap of insight by a computer program I am interacting with will
make it seem, just for a moment, that thinking is taking place.
Now let us consider the most difficult approach. If we define thinking
to involve conscious intentionality, then we may not be in a position to answer the
question at all. I know that I am conscious, so I know that I think (hence Descartes's
famous dictum "I think, therefore I am). I assume that other people think (lest I go
mad), but this assumption appears to be built in (what philosophers would call a priori
knowledge), rather than based on my observations of the behavior of other people. I can
imagine machines that can understand and respond to people and situations with the same
apparent intelligence as real people (see some of the scenarios above). The behavior of
such machines would be indistinguishable from that of people; they would pass any
behavioral test of intelligence, including the Turing test. Are these machines conscious?
Do they have genuine intentionality or free will? Or are they just following their
programs? Is there a distinction to be ma! de between conscious free will and just
following a program? Is this a distinction with a difference? Here we arrive once again at
the crux of a philosophical issue that has been debated for several thousand years. Some
observers, such as Minsky and Dennett, maintain that consciousness is indeed an observable
and measurable facet of bahavior, that we can imagine a test that could in theory
determine whether or not an entity is conscious. Personally, I prefer a more subjective
concept of conciousness, the idea that consciousness is a reality appreciated only by its
possessor. Or perhaps I should say that consciousness is the possessor of the
intelligence, rather than the other way around. If this is confusing, then you are
beginning to appreciate why philosophy has always been so difficult.
If we assume a concept of thinking based on consciousness and hold that
consciousness is detectable in some way, then one only has to carry out the appropriate
experiment and the answer will be at hand. (If someone does this, let me know.) If, on the
other hand, one accepts a subjective view of consciousness, then only the machine itself
could know if it is conscious and thus thinking (assuming it can truly know anything. We
could, of course, ask the machine if it is conscious, but we would not be protected from
the possibility of the machine having been programmed to lie. (The philosopher Michael
Serwin once proposed building an intelligent machine that could not lie and then simply
asking it if it was conscious).
One remaining approach to this question comes to us from quantum
mechanics. In perhaps its most puzzling implication, quantum mechanics actually ascribes a
physical reality to consciousness. Quantum theory states that a particle cannot have both
a precise location and a precise velocity. If we measure its velocity precisely, then its
location becomes inherently imprecise. In other words, its location becomes a probability
cloud of possible locations. The reverse is also true: measuring its precise location
renders its velocity imprecise. It is important to understand exactly what quantum
mechanics is trying to say. It is not saying that there is an underlying reality of an
exact location and velocity and that we are simply unable to measure them both precisely.
It is literally saying that if a conscious being measures the velocity of a particle, it
actually renders the reality of the location of that particle imprecise. Quantum mechanics
is addressing not simply limitations in observation but the impact of conscious
observation on the underlying reality of what is observed. Thus, conscious observation
actually changes a property of a particle. Observation of the same particle by a machine
that was not conscious would not have the same effect. If this seems strange to you, you
are in good company. Einstein found it absurd and rejected it. Quantum mechanics is
consistent with a philosophical tradition that ascribes fundamental reality to knowledge,
as opposed to knowledge simply being a reflection of some other fundamental reality.
Quantum mechanics is more than just a philosophical viewpoint, however: its predictions
have been consistently confirmed. Almost any electronic device of the past 20 years
demonstrates its principles, since the transistor is an embodiment of the paradoxical
predictions of quantum mechanics. Quantum mechanics is the only theory in physics to
ascribe a specific role to consciousness beyond simply saying that consciousness is what
may happen to matter that evolves to high levels of intelligence according to physical
laws.
If one accepts its notions fully, then quantum mechanics may imply a way
to physically detect consciousness. I would counsel caution, however, to any would-be
builder of a consciousness-detector based on these principles. It might be upsetting to
point a quantum-mechanical consciousness detector at ourselves and discover that we are
not really conscious after all.
As a final note on quantum mechanics let me provide a good illustration
of the central role it ascribes to consciousness. According to quantum mechanics,
observing the velocity of a particle affects not only the preciseness of its location but
also affects the preciseness of the location of certain types of "sister"
particles that may have emerged from the same particle interaction that produced the
particle whose velocity we just observed. For example, if an interaction produces a pair
of particles that emerge in opposite directions and if we subsequently observe the
velocity of one of the particles, we will instantly affect the preciseness of the position
of both that particle and its sister, which may be millions of miles away. This would
appear to contradict a fundamental tenet of relativity: that effects cannot be transmitted
faster than the speed of light. This paradox is currently under study.
What impact will the age of intelligent machines have on
society?
When computers were first invented in the mid 1940s, they were generally
regarded as curiosities, though possibly of value to mathematics and a few engineering
disciplines. Their value to science, business, and other disciplines soon became apparent,
and exploration of their practical applications soon began. Today, almost a half-century
later, computers are ubiquitous and highly integrated into virtually all of society's
institutions. If a law were passed banning all computers (and in the doubtful event that
such legislation were adhered to), society would surely collapse. The orderly functioning
of both government and business would break down in chaos. We are already highly dependent
on these "amplifiers of human thought," as Ed Feigenbaum calls them. As the
intelligence of our machines improves and broadens, computer intelligence will become
increasingly integrated into our decision making, our economy, our work, our learning, our
ability to communicate, and our lifestyles. They will be a driving force in shaping our
future world. But the driving force in the growth of machine intelligence will continue to
be human intelligence, at least for the next half century.
A final note
When I was a boy, I had a penchant for collecting magic tricks and was
known to give magic shows for friends and family. I took pleasure in the delight of my
audience in observing apparently impossible phenomena. It became apparent to me that
organizing ordinary methods in just the right sequence could give rise to striking results
that went beyond the methods I started with. I also realized that revealing these methods
would cause the magic to disappear and leave only the ordinary methods.
As I grew older, I discovered a more powerful form of magic: the
computer. Again, by organizing ordinary methods in just the right sequences (that is, with
the right algorithms), I could once again cause delight. Only the delight caused by this
more grown-up magic was more profound. Computerized systems that help overcome the
handicaps of the disabled or provide greater expressiveness and productivity for all of us
provide measures of delight more lasting than the magic tricks of childhood. The sequences
of 1s and 0s that capture the designs and algorithms of our computers embody our future
knowledge and wealth. And unlike more ordinary magic, any revelation of the methods
underlying our computer magic does not tarnish its enchantment.
The Age of Spiritual Machines