Can Computers Think? The Case For and Against Artificial Intelligence


Artificial intelligence has been the subject of many bad "80\'s" movies and
countless science fiction novels. But what happens when we seriously consider
the question of computers that think. Is it possible for computers to have
complex thoughts, and even emotions, like homo sapien? This paper will seek to
answer that question and also look at what attempts are being made to make
artificial intelligence (hereafter called AI) a reality.
Before we can investigate whether or not computers can think, it is
necessary to establish what exactly thinking is. Examining the three main
theories is sort of like examining three religions. None offers enough support
so as to effectively eliminate the possibility of the others being true. The
three main theories are: 1. Thought doesn\'t exist; enough said. 2. Thought
does exist, but is contained wholly in the brain. In other words, the actual
material of the brain is capable of what we identify as thought. 3. Thought is
the result of some sort of mystical phenomena involving the soul and a whole
slew of other unprovable ideas. Since neither reader nor writer is a scientist,
for all intents and purposes, we will say only that thought is what we (as homo
sapien) experience.
So what are we to consider intelligence? The most compelling argument
is that intelligence is the ability to adapt to an environment. Desktop
computers can, say, go to a specific WWW address. But, if the address were
changed, it wouldn\'t know how to go about finding the new one (or even that it
should). So intelligence is the ability to perform a task taking into
consideration the circumstances of completing the task.
So now that we have all of that out of that way, can computers think?
The issue is contested as hotly among scientists as the advantages of Superman
over Batman is among pre-pubescent boys. On the one hand are the scientists who
say, as philosopher John Searle does, that “Programs are all syntax and no
semantics.” (Discover, 106) Put another way, a computer can actually achieve
thought because it “merely follows rules that tell it how to shift symbols
without ever understanding the meaning of those symbols.” (Discover, 106) On
the other side of the debate are the advocates of pandemonium, explained by
Robert Wright in Time thus: “[O]ur brain subconsciously generates competing
theories about the world, and only the ‘winning\' theory becomes part of
consciousness. Is that a nearby fly or a distant airplane on the edge of your
vision? Is that a baby crying or a cat meowing? By the time we become aware of
such images and sounds, these debate have usually been resolved via a winner-
take-all struggle. The winning theory-the one that best matches the data-has
wrested control of our neurons and thus our perceptual field.” (54) So, since
our thought is based on previous experience, computers can eventually learn to
think.
The event which brought this debate in public scrutiny was Garry
Kasparov, reigning chess champion of the world, competing in a six game chess
match against Deep Blue, an IBM supercomputer with 32 microprocessors. Kasparov
eventually won (4-2), but it raised the legitimate question, if a computer can
beat the chess champion of the world at his own game (a game thought of as the
ultimate thinking man\'s game), is there any question of AI\'s legitimacy? Indeed,
even Kasparov said he “could feel-I could smell- a new kind of intelligence
across the table.” (Time, 55) But, eventually everyone, including Kasparov,
realized that what amounts to nothing more than brute force, while impressive,
is not thought. Deep Blue could consider 200 million moves a second. But it
lacked the intuition good human players have. Fred Guterl, writing in Discover,
explains. “Studies have shown that in a typical position, a strong human play
considers on average only two moves. In other words, the player is choosing
between two candidate moves that he intuitively recognizes, based on prior
experience, as contributing to the goals of the position.”
Seeking to go beyond the brute force of Deep Blue in separate projects,
are M.I.T. professor Rodney Brooks and computer scientist Douglas Lenat. The
desire to conquer AI are where the similarities between the two end.
Brooks is working on an AI being nicknamed Cog. Cog has cameras for
eyes, eight 32-bit microprocessors for a brain and soon will have a skin-like
membrane. Brooks is allowing Cog to learn about the world like a baby would. “
It sits there waving its arm, reaching for things.” (Time, 57) Brooks\'s hope
is that by