Can Computers Think The Case For And

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Can Computers Think? The Case For And Against Artificial Intelligence Essay, Research Paper

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 programming and reprogramming itself, Cog will make the leap to

thinking. This expectation is based on what Julian Dibbell, writing in Time,

describes as the ?bottom-up school. Inspired more by biological structures than

by logical ones, the bottom-uppers don’t bother trying to write down the rules

of thought. Instead, they try to conjure thought up by building lots of small,

simple programs and encouraging them to interact.? (57)

Lenat is critical of this type of AI approach. He accuses Brooks of

wandering aimlessly trying to recreate evolution. Lenat has created CYC. An AI

program which uses the top down theory which states that ?if you can write down

the logical structures through which we comprehend the world, you’re halfway to

re-creating intelligence. (Time, 57) Lenat is feeding CYC common sense

statements (i.e. ?Bread is food.?) with the hopes that it will make that leap to

making its own logical deductions. Indeed, CYC can already pick a picture of a

father watching his daughter learn to walk when prompted for pictures of happy

people. Brooks has his own criticisms for Lenat. ?Without sensory input, the

program’s knowledge can never really amount to more than an abstract network of

symbols.

So, what’s the answer? The evidence points to the position that AI is

possible. What is our brain but a complicated network of neurons? And what is

thought but response to stimuli? How to go about achieving AI is another

question entirely. All avenues should be explored. Someone is bound to hit on

it. Thank you.

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