Making a Computer Get Smart		               

                 appeared in Insight Magazine, March 24, 1986

Scientists are teaching a computer to reason out problems and learn from 
experience.  In other words, they are trying to give a computer common sense.  	
They have had limited success, but just to teach a computer how to converse 
requires a breakthrough.

                                  ----------

Inside a gleaming office complex in Austin, Texas, some of the nation's 
brightest scientist, linguists and psychologists are trying to tutor a dumb 
student.

The student is a computer, and a 24-member artificial-intelligence team is 
spoon-feeding it thousands of scraps of knowledge, as well as giving it 
grammar and vocabulary lessons.  Their goal is to cram the machine - a 
mindless array of thumbnail-sized silicon chips - with enough facts, rules of 
thumb and human language skills that it may begin to think and learn on its 
own.

Here, at the Microelectronics and Computer Technology Corp. (MCC), a joint 
research and development venture backed by America's corporate giants, the 
future is being built.

MCC is "pushing back the frontiers of science," says its chairman, retired 
Navy Adm. Bobby R. Inman, who previously served as deputy director of the 
Central Intelligence Agency.

Article by article, the team of researchers is dissecting an encyclopedia, 
then encoding its contents into the computer's memory bank.  For example, all 
the facts presented in an article on flight are encoded, plus the underlying 
knowledge about the world needed to understand the article.

They are feeding the machine thousands of bits and pieces of common sense: If 
you're out in the rain, you get wet.  If you drop something, it falls to the 
ground.  An object can't be in two places at once.  Each person lives for a 
single interval of time.  

They also are teaching the computer about itself.  "It has to understand that 
it is a program," says a scientist.  "It needs to know that a human being is 
watching it."  MCC, which began its high-stakes research in January 1984, is 
owned by 21 U.S. companies, including Rockwell International Corp., Honeywell 
Inc. and Martin Marietta Corp.  MCC's goal is to create a variety of new 
computer technologies for the 1990s and beyond - passing along the fruits of 
its research to its shareholder companies to give them a head start over 
foreign competitors in designing new products and services.

The $65-million-a-year project has resulted in a remarkably high degree of 
cooperation between otherwise archrivals.  At the Austin headquarters, one-
third of MCC's 410 employees are on loan from the various shareholder firms.

MCC has quickly emerged as one of the new heavyweights of artifical 
intelligence (AI), the discipline that has already taught computers to play 
chess and to help perform medical diagnoses. 

Researchers at MCC and a handful of laboratories are trying to build the 
prototype for a fifth-generation computer capable of reasoning its way through 
myriad tasks in the home, at the workplace and on the battlefield.

But when asked to explain what makes machines "intelligent," a computer 
scientist is likely to talk in circles.

" `Artificial intelligence' is trying to do things we don't know how to do 
yet," says Marvin L. Minsky, a pioneer in artificial intelligence at MIT.  
"But that's a working definition.  It changes every year.

"Twenty years ago, having a machine recognize a picture or play chess or 
understand simple language would have been out of reach," he says.  "It's sort 
of a moving horizon." 

Even before the first generation of huge machines powered by vacuum tubes, men 
dreamed of building a computer that could mimic human thought.  But efforts 
over the past 30 years to make such a computer have fallen short.

Powerful, number-crunching computers can analyze vast amounts of data, spit 
out amazing mathematical solutions and guide an unmanned probe to the outer 
reaches of the solar system.  Yet these machines have no inkling of human 
goals and beliefs, no sense of the world or their place in it.

Jonathan Slocum, MCC's director of natural language processing, believes that 
words are a key to machine intelligence.

His reasoning is simple: A child's ability to learn about the world is closely 
tied to his use of words as symbols.  Digital computers have no grasp of the 
meaning of words or what lies beyond them.  And these machines will forever 
lack common sense until they are able to communicate with, and learn from, 
people.

But what might seem like a straightforward task - teaching English to a 
computer by cramming it with grammatical rules, words and definitions - has 
proved a monumental endeavor.

"We would be very happy if these machines were as effective as a 4-year-old 
child with respect to the grammar," says Slocum.  

Home computers can mimic verbal skills by using sentences to display a 
problem's solution.  But faced with interpreting sentences, advance computers 
- which rely on limited vocabularies of narrowly defined words - break down.

Simple conversation, as it turns out, takes an enormous amount of information 
processing at incredibly high speeds.

"We rarely perceive ambiguity in something someone says," says Slocum.  But 
"almost any sentence you hear a human being utter will be ambiguous."

Depending on the context, the word "ball" in a sentence could mean a dance, a 
round object used in sports or a good time.  Similarly, a simple sentence 
might contain 10 words with three definitions each.

" We don't consciously review all the interpretations.  Human beings select 
one and go with it almost all the time," Slocum says.  "If your confidence [in 
your first interpretation] is high, you're not going to stop the speaker.  If 
your confidence is low, you may stop the speaker and ask whether he meant this 
or that." 

Slocum is writing a computer program in which his "linguist's intuition" is 
encoded in plausibility scores: the mathematical probabilities for the 
likelihood that a statement is true.

Dissecting a sentence, his computer program assigns plausibility scores for 
the possible meaning of each word, and then applies rules for combining 
plausibility factors as it examines each element.  Future computers will 
recognize, he says, when to accept at face value its first interpretation of a 
sentence, when to ask for clarification and when to say, "I'm confused."

"Four-year-olds are quite good.  They know most of the grammar that an adult 
does," he says.  "They don't know all the grammatical structures that exist in 
the language, but they know a great majority of them."

It will take a major scientific breakthrough, he says, for computers to use 
metaphors, idioms and similes.  After all, how does a literal-minded machine 
catch the meaning of phrases such as "cry a river of tears," "kick the bucket" 
or "she is like a rose"?

What Slocum's computer program lacks in grammar skills, he hopes to bolster 
with a working vocabulary of 20,000 words.  Future computer programs, using 
complete dictionaries of words and multiple interpretations, will have "vast 
proficiency, out-stripping any human being," he says.

Meanwhile, MCC's artificial-intelligence team is bringing up its baby by 
feeding the computer with more facts about humans, the world and itself.

The computer is a tabula rasa, a blank slate, says Douglas B. Lenat, an 
artificial intelligence project director at MCC.  "We're bootstrapping it up 
to the point where it will be a reasonable student.

"The more you know, the more easily you can learn," he says.  "If you start 
out a [computer] program that knows next to nothing, it's hard for it to 
assimilate new pieces of information.

"But children already know so much about the world that it's very likely that 
they'll have something they can hook new experience onto and thereby relate," 
he says.

Future computers, he says, will examine a problem - for example, a battlefield 
situation - and decide what problem-solving strategy to employ, "introspect" 
to see if they are making progress and take another tack if needed.  

"That kind of behavior leads to something that appears very much like 
consciousness," he says, which he defines as "largely the ability to 
introspect on what your doing."

Computer programs "have a form of consciousness," he says.  "They have to be 
conscious of why the do what they do.  You can stop it at any point and ask, 
`Why did you do that?' and it will tell you, after a fashion."

But a new generation of superfast computers with huge memory banks will be 
required if machines are to learn English and become smarter.

Researchers at MCC and a few other U.S. and Japanese laboratories are 
developing "parallel processors": networks of tens, hundreds and even 
thousands of computer chips, each with a separate memory bank, that work in 
concert to solve a problem.

Others are creating new computer languages for parallel computers that can 
correctly divide problems into subproblems - for instance, examining different 
parts of a sentence.

Lenat hopes that 10 years from now, MCC will have taken a giant step toward 
building a new generation of machines with some degree of common sense.  "But 
until computers are smarter than they are now," he says, "most questions they 
ask will be stupid."

It is only a matter of time before the smart machines arrive.

As the pace of new technology accelerates, scientists at the world's top 
research laboratories are locked in a high-stakes computer race.

We are attempting to make machines capable of enormous amounts of knowledge, 
more than any human can muster," says MCC's Slocum.  "And these machines will 
have enormous amount of power."

According to various experts, "thinking" machines of the 21st century may 
range from huge data banks to crude vision, hearing and speech systems 
installed in factory robots.

At home, future computers may act as general problem solvers, time managers 
and consultants on matters ranging from taxes to medical problems to assisting 
with a person's daily schedule.  Truly user-friendly, these machines may speak 
English and respond to spoken commands.

Industrial and government computers may be used for everything form handling 
air traffic control systems at busy airports to finding ways to pay off the 
national debt.

Commercial robots operated by computer programs may scour the ocean floor for 
manganese nodules, clean radioactive spills and toil in hazardous coal mines.

Military robots may be ready to serve in other hostile situations like 
chemical or nuclear war zones.  Unmanned fighter aircraft, tanks, ships and 
submarines may be activated simply by voice commands.

Powerful defense computers may help contain and resolve small conflicts 
between nations by automatically interpreting 24-hour-a-day surveillance data 
from various land, sea, air and space sensors - foiling the possibility of 
suprise attacks.

In addition, spaceborne computers able to instantaneously detect, target and 
defend against thousands of enemy warheads may provide the linchpin for the 
Strategic Defense Initiative, The so-called "star wars" antiballistic missle 
shield.

These computers would have to distinguish in seconds between real attacks and 
routine space launches, as well as discriminate between decoys and warheads, 
before automatically launching particle beams to neutralize enemy warheads.  
No computer system currently exists that is capable of handling this awesome 
task, but some defense experts believe that breakthroughs in "intelligent" 
software and high-speed parallel computers could make the difference.

"over the next 100 years there will be fantastic progress," says Minsky, the 
artificial-intelligence pioneer.  "Machines will do miraculous things.  I'm 
sure they'll be flying airplanes better than people.

"To [use] a gruesome image, it's like slavery.  Machines will do whatever 
people want them to do."

The trick to building the most helpful computers is to endow them with common 
sense and learning skills, he says, "so you don't have to program them 
yourself.  Getting them to think well is the problem.  It's probably the 
hardest problem science has ever faced.  And it won't happen overnight."

The international race for computer supremacy may determine which nations hold 
scientific, economic and military dominance well into the next century.

"The U.S hasn't lost its lead in the ability to create new technologies.  But 
our lead is somewhat diminished," says MCC's Inman.

MCC was created in the wake of Japan's announcement in 1980 that it would 
launch a major, national effort to surpass the United States' technological 
edge.  Japan's Fifth Generation Project is aimed at building a "supercomputer" 
for high-speed numerical calculations, as well as artificial-intelligence 
software for a supersmart computer capable of solving non-numerical problems.  
Joining the race, European technology firms also recently began their own 
cooperative research project called Espirit.  But already, some 500 "expert 
systems" are at work outside the laboratory in the marketplace - performing a 
wide range of tasks from monitoring nuclear reactors to pinpointing the 
location of mineral deposits.

These primitive computer programs mimic human reasoning by quickly solving 
routine yet highly complex problems involving expert knowledge in a particular 
discipline.

Expert systems are helping to diagnose bacterial infections, to predict crop 
irrigation needs, to design electronic circuits and to control the treatment 
of patients in intensive care.

And expert software is available for personal computers to help people make 
financial planning decisions and to negotiate successfully at home and on the 
job.

By 1990, the industrial and home market for expert systems is expected to grow 
to $2 billion in sales.  Yet despite their success, expert systems have narrow 
applications.  Faced with anything outside their limited field of expertise, 
these fragile programs get confused. 

These systems emulate only a slice of human intelligence.  They are unable to 
learn from experience or to handle nonrecurring problems.  The bulk of their 
expert knowledge depends on simple sets of "if-then" rules, such as: "If a 
child has blisters and if it has a fever, then it may have chicken pox."

An electronic cardiologist, for example, can offer near-human advice on 
medical treatment.  But it has no idea of what a patient is, let alone a human 
being.

"If a patient has a disease that's outside the expertise of the expert system, 
there's no telling what diagnosis it will come up with," says MCC's Slocum.  
"if the doctor follows the diagnosis, some disastrous things could happen.

"Any reasonable person with a small amount of modesty knows when he's out of 
his depth," he says.  "We're trying to program computers to have a general 
knowledge of the world, coupled with self-knowledge, so the machine can gauge 
its limitations."

This "intelligent" software, he says, is designed to bolster expert systems 
with "the common sense that a human being would bring to bear" on a problem.

A few experimental computer programs already have been built that analyze 
novel problems, make guesses by using rules of thumb learned from analogous 
situations and test their hypotheses by conducting experiments.

Meanwhile, the Defense Department is funding a variety of artificial-
intelligence projects, including the development of an unmanned vehicle.  
Using machine vision, it may act as a mobile sentry or ferry supplies and 
weapons across rough terrain.

The Defense Department also has funded research into voice-activated command 
and control systems, vision systems to guide missiles to targets, and computer 
aids for fighter pilots, tank drivers and battlefield commanders to help them 
quickly make complex decisions.

Artificial-intelligence researchers, often voracious readers of science 
fiction, envision a future in which man reaches new heights with the aid of 
brilliant and not-so-smart machines.  They see a future in which cheap 
industrial robots perform mundane and hazardous jobs - working in unmanned 
factories, repairing satellites in space and disposing of nuclear wastes. 

Private industry is already using robots as spray painters, spot welders and 
assembly-line inspectors.  General Motors Corp. is developing machine vision 
systems that may enable robots to move more like people in the workplace.

The new technology will not be without a human price.  Imagine the 
psychological impact on a highly skilled, middle-aged welder who is taken off 
his job because a machine does it better.

A proliferation of smart computers and related technologies in advance nations 
also may spark new political tensions with the Third World.

"The pace of change by emerging technologies is likely to be somewhat faster 
over the next 10 to 15 years that it's been over the past 30 years," says 
Inman.  "In the early years, there's clearly going to be an even wider gap 
between the haves and the have-nots."

MCC's Lenat forsees the eventual development of a "global knowledge base": a 
vast information bank that people can tap into with portable links.  Computers 
will serve as "intelligence amplifiers to help us think faster and better than 
we were ever able to," he says.  "They will provide an opportunity to enhance 
ourselves."

As progress in artificial-intelligence research accelerates, people may face 
som mind-boggling questions.  Could machines ever be capable of inspiration or 
insight - that sudden flash of recognition you experience when you finally 
solve a tough problem?

"I believe the process we are embarking on will demystify intuition," says 
Lenat.  "Intuition is often just analogizing to other situations to come up 
with an approximate answer very quickly."

Will computers ever attain any sort of self-awareness?  Could they be 
programmed to know the meaning of love or honor?  Could they ever appreciate 
or even recognize humor?  And finally, to what extent should we rely on these 
machines?

"No more and no less than people whose insides we don't have access to, 
either," says Lenat.  "We [should] use performance to measure the degree of 
trust."

"The net effect of [artificial-intelligence] will be positive.  It will save 
lives," he says.  "It will increase human productivity, including the amount 
of food in the world...all sorts of positive things and a few negative ones."

Computer systems that increase the warning time of military attack, he says, 
will prolong the time for political response and negotiation.

"[And] if you're going to send out a tank," he says, "it's better that a human 
is not in it."

					- J.H. Doyle