AI lost in the woods?

July/August 2007
Technology Review

Artificial Intelligence Is Lost in the Woods
A conscious mind will never be built out of software, argues a Yale
University professor.


By David Gelernter


Artificial Intelligence Is Lost in the Woods
************************************************************


Artificial intelligence has been obsessed with several questions from
the start: Can we build a mind out of software? If not, why not? If
so, what kind of mind are we talking about? A conscious mind? Or an
unconscious intelligence that seems to think but experiences nothing
and has no inner mental life? These questions are central to our view
of computers and how far they can go, of computation and its ultimate
meaning--and of the mind and how it works.


They are deep questions with practical implications. AI researchers
have long maintained that the mind provides good guidance as we
approach subtle, tricky, or deep computing problems. Software today
can cope with only a smattering of the information-processing
problems
that our minds handle routinely--when we recognize faces or pick
elements out of large groups based on visual cues, use common sense,
understand the nuances of natural language, or recognize what makes a
musical cadence final or a joke funny or one movie better than
another. AI offers to figure out how thought works and to make that
knowledge available to software designers.


It even offers to deepen our understanding of the mind itself.
Questions about software and the mind are central to cognitive
science
and philosophy. Few problems are more far-reaching or have more
implications for our fundamental view of ourselves.


The current debate centers on what I'll call a "simulated conscious
mind" versus a "simulated unconscious intelligence." We hope to learn
whether computers make it possible to achieve one, both, or neither.


I believe it is hugely unlikely, though not impossible, that a
conscious mind will ever be built out of software. Even if it could
be, the result (I will argue) would be fairly useless in itself. But
an unconscious simulated intelligence certainly could be built out of
software--and might be useful. Unfortunately, AI, cognitive science,
and philosophy of mind are nowhere near knowing how to build one.
They
are missing the most important fact about thought: the "cognitive
continuum" that connects the seemingly unconnected puzzle pieces of
thinking (for example analytical thought, common sense, analogical
thought, free association, creativity, hallucination). The cognitive
continuum explains how all these reflect different values of one
quantity or parameter that I will call "mental focus" or
"concentration"--which changes over the course of a day and a
lifetime.


Without this cognitive continuum, AI has no comprehensive view of
thought: it tends to ignore some thought modes (such as free
association and dreaming), is uncertain how to integrate emotion and
thought, and has made strikingly little progress in understanding
analogies--which seem to underlie creativity.


My case for the near-impossibility of conscious software minds
resembles what others have said. But these are minority views. Most
AI
researchers and philosophers believe that conscious software minds
are
just around the corner. To use the standard term, most are
"cognitivists." Only a few are "anticognitivists." I am one. In fact,
I believe that the cognitivists are even wronger than their opponents
usually say.


But my goal is not to suggest that AI is a failure. It has merely
developed a temporary blind spot. My fellow anticognitivists have
knocked down cognitivism but have done little to replace it with new
ideas. They've showed us what we can't achieve (conscious software
intelligence) but not how we can create something less dramatic but
nonetheless highly valuable: unconscious software intelligence. Once
AI has refocused its efforts on the mechanisms (or algorithms) of
thought, it is bound to move forward again.


Until then, AI is lost in the woods.


What Is Consciousness?
In conscious thinking, you experience your thoughts. Often they are
accompanied by emotions or by imagined or remembered images or other
sensations. A machine with a conscious (simulated) mind can feel
wonderful on the first fine day of spring and grow depressed as
winter
sets in. A machine that is capable only of unconscious intelligence
"reads" its thoughts as if they were on cue cards. One card might
say,
"There's a beautiful rose in front of you; it smells sweet." If
someone then asks this machine, "Seen any good roses lately?" it can
answer, "Yes, there's a fine specimen right in front of me." But it
has no sensation of beauty or color or fragrance. It has no
experiences to back up the currency of its words. It has no inner
mental life and therefore no "I," no sense of self.


But if an artificial mind can perform intellectually just like a
human, does consciousness matter? Is there any practical, perceptible
advantage to simulating a conscious mind?


Yes.


An unconscious entity feels nothing, by definition. Suppose we ask
such an entity some questions, and its software returns correct
answers.


"Ever felt friendship?" The machine says, "No."


"Love?" "No." "Hatred?" "No." "Bliss?" "No."


"Ever felt hungry or thirsty?" "Itchy, sweaty, -tickled, excited,
conscience stricken?"


"Ever mourned?" "Ever rejoiced?"


No, no, no, no.


In theory, a conscious software mind might answer "yes" to all these
questions; it would be conscious in the same sense you are (although
its access to experience might be very different, and strictly
limited).


So what's the difference between a conscious and an unconscious
software intelligence? The potential human presence that might exist
in the simulated conscious mind but could never exist in the
unconscious one.


You could never communicate with an unconscious intelligence as you
do
with a human--or trust or rely on it. You would have no grounds for
treating it as a being toward which you have moral duties rather than
as a tool to be used as you like.


But would a simulated human presence have practical value? Try asking
lonely people--and all the young, old, sick, hurt, and unhappy people
who get far less attention than they need. A made-to-order human
presence, even though artificial, might be a godsend.


AI (I believe) won't ever produce one. But it can still lead the way
to great advances in computing. An unconscious intelligence might be
powerful. Alan -Turing, the great English mathematician who founded
AI, seemed to believe (sometimes) that consciousness was not central
to thought, simulated or otherwise.


He discussed consciousness in the celebrated 1950 paper in which he
proposed what is now called the "Turing test." The test is meant to
determine whether a computer is "intelligent," or "can think"--terms
Turing used interchangeably. If a human "interrogator" types
questions, on any topic whatever, that are sent to a computer in a
back room, and the computer sends back answers that are
indistinguishable from a human being's, then we have achieved AI, and
our computer is "intelligent": it "can think."


Does artificial intelligence require (or imply the existence of)
artificial consciousness? Turing was cagey on these questions. But he
did write,


I do not wish to give the impression that I think there is no
mystery about consciousness. There is, for instance, something of a
paradox connected with any attempt to localise it. But I do not think
these mysteries necessarily need to be solved before we can answer
the
question with which we are concerned in this paper.


That is, can we build intelligent (or thinking) computers, and how
can
we tell if we have succeeded? -Turing seemed to assert that we can
leave consciousness aside for the moment while we attack simulated
thought.


But AI has grown more ambitious since then. Today, a substantial
number of researchers believe one day we will build conscious
software
minds. This group includes such prominent thinkers as the inventor
and
computer scientist Ray Kurzweil. In the fall of 2006, Kurzweil and I
argued the point at MIT, in a debate sponsored by the John Templeton
Foundation. This piece builds, in part, on the case I made there.


A Digital Mind
The goal of cognitivist thinkers is to build an artificial mind out
of
software running on a digital computer.


Why does AI focus on digital computers exclusively, ignoring other
technologies? For one reason, because computers seemed from the first
like "artificial brains," and the first AI programs of the 1950s--the
"Logic Theorist," the "Geometry Theorem-Proving Machine"--seemed at
their best to be thinking. Also, computers are the characteristic
technology of the age. It is only natural to ask how far we can push
them.


Then there's a more fundamental reason why AI cares specifically
about
digital computers: computation underlies today's most widely accepted
view of mind. (The leading technology of the day is often pressed
into
service as a source of ideas.)


The ideas of the philosopher Jerry Fodor make him neither strictly
cognitivist nor anticognitivist. In The Mind Doesn't Work That Way
(2000), he discusses what he calls the "New Synthesis"--a broadly
accepted view of the mind that places AI and cognitivism against a
biological and Darwinian backdrop. "The key idea of New Synthesis
psychology," writes Fodor, "is that cognitive processes are
computational. ... A computation, according to this understanding, is
a formal operation on syntactically structured representations." That
is, thought processes depend on the form, not the meaning, of the
items they work on.


In other words, the mind is like a factory machine in a 1940s
cartoon,
which might grab a metal plate and drill two holes in it, flip it
over
and drill three more, flip it sideways and glue on a label, spin it
around five times, and shoot it onto a stack. The machine doesn't
"know" what it's doing. Neither does the mind.


Likewise computers. A computer can add numbers but has no idea what
"add" means, what a "number" is, or what "arithmetic" is for. Its
actions are based on shapes, not meanings. According to the New
Synthesis, writes Fodor, "the mind is a computer."


But if so, then a computer can be a mind, can be a conscious mind--if
we supply the right software. Here's where the trouble starts.
Consciousness is necessarily subjective: you alone are aware of the
sights, sounds, feels, smells, and tastes that flash past "inside
your
head." This subjectivity of mind has an important consequence: there
is no objective way to tell whether some entity is conscious. We can
only guess, not test.


Granted, we know our fellow humans are conscious; but how? Not by
testing them! You know the person next to you is conscious because he
is human. You're human, and you're conscious--which moreover seems
fundamental to your humanness. Since your neighbor is also human, he
must be conscious too.


So how will we know whether a computer running fancy AI software is
conscious? Only by trying to imagine what it's like to be that
computer; we must try to see inside its head.


Which is clearly impossible. For one thing, it doesn't have a head.
But a thought experiment may give us a useful way to address the
problem. The "Chinese Room" argument, proposed in 1980 by John
Searle,
a philosophy professor at the University of California, Berkeley, is
intended to show that no computer running software could possibly
manifest understanding or be conscious. It has been controversial
since it first appeared. I believe that Searle's argument is
absolutely right--though more elaborate and oblique than necessary.


Searle asks us to imagine a program that can pass a Chinese Turing
test--and is accordingly fluent in Chinese. Now, someone who knows
English but no Chinese, such as Searle himself, is shut up in a room.
He takes the Chinese-understanding software with him; he can execute
it by hand, if he likes.


Imagine "conversing" with this room by sliding questions under the
door; the room returns written answers. It seems equally fluent in
English and Chinese. But actually, there is no understanding of
Chinese inside the room. Searle handles English questions by relying
on his knowledge of English, but to deal with Chinese, he executes an
elaborate set of simple instructions mechanically. We conclude that
to
behave as if you understand Chinese doesn't mean you do.


But we don't need complex thought experiments to conclude that a
conscious computer is ridiculously unlikely. We just need to tackle
this question: What is it like to be a computer running a complex AI
program?


Well, what does a computer do? It executes "machine instructions"--
low-
level operations like arithmetic (add two numbers), comparisons
(which
number is larger?), "branches" (if an addition yields zero, continue
at instruction 200), data movement (transfer a number from one place
to another in memory), and so on. Everything computers accomplish is
built out of these primitive instructions.


So what is it like to be a computer running a complex AI program?
Exactly like being a computer running any other kind of program.


Computers don't know or care what instructions they are executing.
They deal with outward forms, not meanings. Switching applications
changes the output, but those changes have meaning only to humans.
Consciousness, however, doesn't depend on how anyone else interprets
your actions; it depends on what you yourself are aware of. And the
computer is merely a machine doing what it's supposed to do--like a
clock ticking, an electric motor spinning, an oven baking. The oven
doesn't care what it's baking, or the computer what it's computing.


The computer's routine never varies: grab an instruction from memory
and execute it; repeat until something makes you stop.


Of course, we can't know literally what it's like to be a computer
executing a long sequence of instructions. But we know what it's like
to be a human doing the same. Imagine holding a deck of cards. You
sort the deck; then you shuffle it and sort it again. Repeat the
procedure, ad infinitum. You are doing comparisons (which card comes
first?), data movement (slip one card in front of another), and so
on.
To know what it's like to be a computer running a sophisticated AI
application, sit down and sort cards all afternoon. That's what it's
like.


If you sort cards long enough and fast enough, will a brand-new
conscious mind (somehow) be created? This is, in effect, what
cognitivists believe. They say that when a computer executes the
right
combination of primitive instructions in the right way, a new
conscious mind will emerge. So when a person executes the right
combination of primitive instructions in the right way, a new
conscious mind should (also) emerge; there's no operation a computer
can do that a person can't.


Of course, humans are radically slower than computers. Cognitivists
argue that sure, you know what executing low-level instructions
slowly
is like; but only when you do them very fast is it possible to create
a new conscious mind. Sometimes, a radical change in execution speed
does change the qualitative outcome. (When you look at a movie frame
by frame, no illusion of motion results. View the frames in rapid
succession, and the outcome is different.) Yet it seems arbitrary to
the point of absurdity to insist that doing many primitive operations
very fast could produce consciousness. Why should it? Why would it?
How could it? What makes such a prediction even remotely plausible?


But even if researchers could make a conscious mind out of software,
it wouldn't do them much good.


Suppose you could build a conscious software mind. Some cognitivists
believe that such a mind, all by itself, is AI's goal. Indeed, this
is
the message of the Turing test. A computer can pass Turing's test
without ever mingling with human beings.


But such a mind could communicate with human beings only in a
drastically superficial way.


It would be capable of feeling emotion in principle. But we feel
emotions with our whole bodies, not just our minds; and it has no
body. (Of course, we could say, then build it a humanlike body! But
that is a large assignment and poses bioengineering problems far
beyond and outside AI. Or we could build our new mind a body unlike a
human one. But in that case we couldn't expect its emotions to be
like
ours, or to establish a common ground for communication.)


Consider the low-energy listlessness that accompanies melancholy, the
overflowing jump-for-joy sensation that goes with elation, the
pounding heart associated with anxiety or fear, the relaxed calm when
we are happy, the obvious physical manifestations of excitement--and
other examples, from rage to panic to pity to hunger, thirst,
tiredness, and other conditions that are equally emotions and bodily
states. In all these cases, your mind and body form an integrated
whole. No mind that lacked a body like yours could experience these
emotions the way you do.


No such mind could even grasp the word "itch."


In fact, even if we achieved the bioengineering marvel of a synthetic
human body, our problems wouldn't be over. Unless this body
experienced infancy, childhood, and adolescence, as humans do--unless
it could grow up, as a member of human society--how could it
understand what it means to "feel like a kid in a candy shop" or to
"wish I were 16 again"? How could it grasp the human condition in its
most basic sense?


A mind-in-a-box, with no body of any sort, could triumphantly pass
the
Turing test--which is one index of the test's superficiality.
Communication with such a contrivance would be more like a parody of
conversation than the real thing. (Even in random Internet chatter,
all parties know what it's like to itch, and scratch, and eat, and be
a child.) Imagine talking to someone who happens to be as articulate
as an adult but has less experience than a six-week-old infant. Such
a
"conscious mind" has no advantage, in itself, over a mere unconscious
intelligence.


But there's a solution to these problems. Suppose we set aside the
gigantic chore of building a synthetic human body and make do with a
mind-in-a-box or a mind-in-an-anthropoid-robot, equipped with video
cameras and other sensors--a rough approximation of a human body. Now
we choose some person (say, Joe, age 35) and simply copy all his
memories and transfer them into our software mind. Problem solved.
(Of
course, we don't know how to do this; not only do we need a complete
transcription of Joe's memories, we need to translate them from the
neural form they take in Joe's brain to the software form that our
software mind understands. These are hard, unsolved problems. But no
doubt we will solve them someday.)


Nonetheless: understand the enormous ethical burden we have now
assumed. Our software mind is conscious (by assumption) just as a
human being is; it can feel pleasure and pain, happiness and sadness,
ecstasy and misery. Once we've transferred Joe's memories into this
artificial yet conscious being, it can remember what it was like to
have a human body--to feel spring rain, stroke someone's face, drink
when it was thirsty, rest when its muscles were tired, and so forth.
(Bodies are good for many purposes.) But our software mind has lost
its body--or had it replaced by an elaborate prosthesis. What
experience could be more shattering? What loss could be harder to
bear? (Some losses, granted, but not many.) What gives us the right
to
inflict such cruel mental pain on a conscious being?


In fact, what gives us the right to create such a being and treat it
like a tool to begin with? Wherever you stand on the religious or
ethical spectrum, you had better be prepared to tread carefully once
you have created consciousness in the laboratory.


The Cognitivists' Best Argument
But not so fast! say the cognitivists. Perhaps it seems arbitrary and
absurd to assert that a conscious mind can be created if certain
simple instructions are executed very fast; yet doesn't it also seem
arbitrary and absurd to claim that you can produce a conscious mind
by
gathering together lots of neurons?


The cognitivist response to my simple thought experiment ("Imagine
you're a computer") might run like this, to judge from a recent book
by a leading cognitivist philosopher, Daniel C. Dennett. Your mind is
conscious; yet it's built out of huge numbers of tiny unconscious
elements. There are no raw materials for creating consciousness
except
unconscious ones.


Now, compare a neuron and a yeast cell. "A hundred kilos of yeast
does
not wonder about Braque," writes Dennett, "... but you do, and you
are
made of parts that are fundamentally the same sort of thing as those
yeast cells, only with different tasks to perform." Many neurons add
up to a brain, but many yeast cells don't, because neurons and yeast
cells have different tasks to perform. They are programmed
differently.


In short: if we gather huge numbers of unconscious elements together
in the right way and give them the right tasks to perform, then at
some point, something happens, and consciousness emerges. That's how
your brain works. Note that neurons work as the raw material, but
yeast cells don't, because neurons have the right tasks to perform.
So
why can't we do the same thing using software elements as raw
materials--so long as we give them the right tasks to perform? Why
shouldn't something happen, and yield a conscious mind built out of
software?


Here is the problem. Neurons and yeast cells don't merely have
"different tasks to perform." They perform differently because they
are chemically different.


One water molecule isn't wet; two aren't; three aren't; 100 aren't;
but at some point we cross a threshold, something happens, and the
result is a drop of water. But this trick only works because of the
chemistry and physics of water molecules! It won't work with just any
kind of molecule. Nor can you take just any kind of molecule, give it
the right "tasks to perform," and make it a fit raw material for
producing water.


The fact is that the conscious mind emerges when we've collected many
neurons together, not many doughnuts or low-level computer
instructions. Why should the trick work when I substitute simple
computer instructions for neurons? Of course, it might work. But
there
isn't any reason to believe it would.


My fellow anticognitivist John Searle made essentially this argument
in a paper that referred to the "causal properties" of the brain. His
opponents mocked it as reactionary stuff. They asserted that since
Searle is unable to say just how these "causal properties" work, his
argument is null and void. Which is nonsense again. I don't need to
know anything at all about water molecules to realize that large
groups of them yield water, whereas large groups of krypton atoms
don't.


Why the Cognitive Spectrum Is More Exciting than Consciousness
To say that building a useful conscious mind is highly unlikely is
not
to say that AI has nothing worth doing. Consciousness has been a
"mystery" (as Turing called it) for thousands of years, but the mind
holds other mysteries, too. Creativity is one of the most important;
it's a brick wall that psychology and philosophy have been banging
their heads against for a long time. Why should two people who seem
roughly equal in competence and intelligence differ dramatically in
creativity? It's widely agreed that discovering new analogies is the
root (or one root) of creativity. But how are new analogies
discovered? We don't know. In his 1983 classic The Modularity of
Mind,
Jerry Fodor wrote, "It is striking that, while everybody thinks
analogical reasoning is an important ingredient in all sorts of
cognitive achievements that we prize, nobody knows anything about how
it works."


Furthermore, to speak of the mystery of consciousness makes
consciousness sound like an all-or-nothing proposition. But how do we
explain the different kinds of consciousness we experience?
"Ordinary"
consciousness is different from your "drifting" state when you are
about to fall asleep and you register external events only vaguely.
Both are different from hallucination as induced by drugs, mental
illness--or life. We hallucinate every day, when we fall asleep and
dream.


And how do we explain the difference between a child's consciousness
and an adult's? Or the differences between child-style and adult-
style
thinking? Dream thought is different from drifting or free--
associating pre-sleep thought, which is different from "ordinary"
thought. We know that children tend to think more concretely than
adults. Studies have also suggested that children are better at
inventing metaphors. And the keenest of all observers of human
thought, the English Romantic poets, suggest that dreaming and waking
consciousness are less sharply distinguished for children than for
adults. Of his childhood, Wordsworth writes (in one of the most
famous
short poems in English), "There was a time when meadow, grove, and
stream, / The earth, and every common sight, / To me did seem /
Apparelled in celestial light, / The glory and the freshness of a
dream."


Today's cognitive science and philosophy can't explain any of these
mysteries.


The philosophy and science of mind has other striking blind spots,
too. AI researchers have been working for years on common sense.
Nonetheless, as Fodor writes in The Mind Doesn't Work That Way, "the
failure of artificial intelligence to produce successful simulations
of routine commonsense cognitive competences is notorious, not to say
scandalous." But the scandal is wider than Fodor reports. AI has been
working in recent years on emotion, too, but has yet to understand
its
integral role in thought.


In short, there are many mysteries to explain--and many "cognitive
competences" to understand. AI--and software in general--can profit
from progress on these problems even if it can't build a conscious
computer.


These observations lead me to believe that the "cognitive
continuum" (or, equally, the consciousness continuum) is the most
important and exciting research topic in cognitive science and
philosophy today.


What is the "cognitive continuum"? And why care about it? Before I
address these questions, let me note that the cognitive continuum is
not even a scientific theory. It is a "prescientific theory"--like
"the earth is round."


Anyone might have surmised that the earth is round, on the basis of
everyday observations--especially the way distant ships sink
gradually
below (or rise above) the horizon. No special tools or training were
required. That the earth is round leaves many basic phenomena
unexplained: the tides, the seasons, climate, and so on. But unless
we
know that the earth is round, it's hard to progress on any of these
problems.


The cognitive continuum is the same kind of theory. I don't claim
that
it's a millionth as important as the earth's being round. But for me
as a student of human thought, it's at least as exciting.


What is this "continuum"? It's a spectrum (the "cognitive spectrum")
with infinitely many intermediate points between two endpoints.


When you think, the mind assembles thought trains--sequences of
distinct thoughts or memories. (Sometimes one blends into the next,
and sometimes our minds go blank. But usually we can describe the
train that has just passed.) Sometimes our thought trains are
assembled--so it seems--under our conscious, deliberate control.
Other
times our thoughts wander, and the trains seem to assemble
themselves.
If we start with these observations and add a few simple facts about
"cognitive behavior," a comprehensive picture of thought emerges
almost by itself.


Obviously, you must be alert to think analytically. To solve a set of
mathematical equations or follow a proof, you need to focus your
attention. Your concentration declines as you grow tired over the
day.


And your mind is in a strange state just before you fall asleep: a
free-associative state in which, rather than following from another
logically, one thought "suggests" the next. In this state, you cannot
focus: if you decide to think about one thing, you soon find yourself
thinking about something else (which was "suggested" by thing one),
and then something else, and so on. In fact, cognitive psychologists
have discovered that we start to dream before we fall asleep. So the
mental state right before sleep is the state of dreaming.


Since we start the day in one state (focused) and finish in another
(free-associating, unfocused), the two must be connected. Over the
day, focus declines--perhaps steadily, perhaps in a series of
oscillations.


Which suggests that there is a continuum of mental states between
highest focus and lowest. Your "focus level" is a large factor in
determining your mode of thought (or of consciousness) at any moment.
This spectrum must stretch from highest-focus thought (best for
reasoning or analysis) downward into modes based more on experience
or
common sense than on abstract reasoning; down further to the relaxed,
drifting thought that might accompany gazing out a window; down
further to the uncontrolled free association that leads to dreaming
and sleep--where the spectrum bottoms out.


Low focus means that your tendency (not necessarily your ability) to
free-associate increases. A wide-awake person can free-associate if
he
tries; an exhausted person has to try hard not to free-associate. At
the high end, you concentrate unless you try not to. At the low end,
you free-associate unless you try not to.


Notice that the role of associative recollection--in which one
thought
or memory causes you to recall another--increases as you move down-
spectrum. Reasoning works (theoretically) from first principles. But
common sense depends on your recalling a familiar idea or technique,
or a previous experience. When your mind drifts as you look out a
window, one recollection leads to another, and to a third, and
onward--
but eventually you return to the task at hand. Once you reach the
edge
of sleep, though, free association goes unchecked. And when you
dream,
one character or scene transforms itself into another smoothly and
illogically--just as one memory transforms itself into another in
free
association. Dreaming is free association "from the inside."


At the high-focus end, you assemble your thought train as if you were
assembling a comic strip or a story-board. You can step back and
"see"
many thoughts at once. (To think analytically, you must have your
premises, goal, and subgoals in mind.) At the high-focus end, you
manipulate your thoughts as if they were objects; you control the
train.


At the bottom, it's just the opposite. You don't control your
thoughts. You say, "my mind is wandering," as if you and your mind
were separate, as if your thoughts were roaming around by themselves.


If at high focus you manipulate your thoughts "from the outside," at
low focus you step into each thought as if you were entering a room;
you inhabit it.That's what hallucination means. The opposite of high
focus, where you control your thoughts, is hallucination--where your
thoughts control you. They control your perceived environment and
experiences; you "inhabit" each in turn. (We sometimes speak of
"surrendering" to sleep; surrendering to your thoughts is the
opposite
of controlling them.)


At the high-focus end, your "I" is separate from your thought train,
observing it critically and controlling it. At the low end, your "I"
blends into it (or climbs aboard).


The cognitive continuum is, arguably, the single most important fact
about thought. If we accept its existence, we can explain and can
model (say, in software) the dynamics of thought. Thought styles
change throughout the day as our focus level changes. (Focus levels
depend, in turn, partly on personality and intelligence: some people
are capable of higher focus; some are more comfortable in higher-
focus
states.)


It also seems logical to surmise that cognitive maturing increases
the
focus level you are able to reach and sustain--and therefore
increases
your ability and tendency to think abstractly.


Even more important: if we accept the existence of the spectrum, an
explanation and model of analogy discovery--thus, of creativity--
falls
into our laps.


As you move down-spectrum, where you inhabit (not observe) your
thoughts, you feel them. In other words, as you move down-spectrum,
emotions emerge. Dreaming, at the bottom, is emotional.


Emotions are a powerful coding or compression device. A bar code can
encapsulate or encode much information. An emotion is a "mental bar
code" that encapsulates a memory. But the function E(m)--the
"emotion"
function that takes a memory m and yields the emotion you in
particular feel when you think about m--does not generate unique
values. Two different-seeming memories can produce the same emotion.


How do we invent analogies? What made -Shakespeare write, "Shall I
compare thee to a summer's day?" Shakespeare's lady didn't look like
a
summer's day. (And what does a "summer's day" look like?)


An analogy is a two-element thought train--"a summer's day" followed
by the memory of some person. Why should the mind conjure up these
two
elements in succession? What links them?


Answer: in some cases (perhaps in many), their "emotional bar codes"
match--or were sufficiently similar that one recalled the other. The
lady and the summer's day made the poet feel the same sort of way.


We experience more emotions than we can name. "Mildly happy,"
"happy,"
"ebullient," "elated"; our choice of English words is narrow. But how
do you feel when you are about to open your mailbox, expecting a
letter that will probably bring good news but might be crushing? When
you see a rhinoceros? These emotions have no names. But each
"represents" or "encodes" some collection of circumstances. Two
experiences that seem to have nothing in common might awaken--in you
only--the same emotion. And you might see, accordingly, an analogy
that no one else ever saw.


The cognitive spectrum suggests that analogies are created by shared
emotion--the linking of two thoughts with shared or similar emotional
content.


To build a simulated unconscious mind, we don't need a computer with
real emotions; simulated emotions will do. Achieving them will be
hard. So will representing memories (with all their complex "multi-
media" data).


But if we take the route Turing hinted at back in 1950, if we forget
about consciousness and concentrate on the process of thought,
there's
every reason to believe that we can get AI back on track--and that AI
can produce powerful software and show us important things about the
human mind.


David Gelernter is a professor of computer science at Yale University
and a national fellow of the American Enterprise Institute.
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http://www.technologyreview.com/Infotech/18867/page1/
Copyright Technology Review 2007.


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