
      NATURAL VERSUS ARTIFICIAL
  You have what's called natural intelligence (except when your 
friends accuse you of having ``natural stupidity''). The 
intelligence of a computer, by contrast, is artificial. Can the 
computer's artificial intelligence ever match yours?
  For example, can the computer ever develop the ``common sense'' 
needed to handle exceptions, such as a broken traffic light? 
After waiting at a red light for several hours, the typical human 
would realize the light was broken. The human would try to 
proceed past the intersection, cautiously. Would a computer 
programmed to ``never go on red'' be that smart?
  Researchers who study the field of artificial intelligence have 
invented robots and many other fascinating computerized devices. 
They've also been trying to develop computers that can understand 
ordinary English commands and questions, so you won't have to 
learn a ``programming language''. They've been trying to develop 
expert systems ___ computers that imitate human experts such as 
doctors and lawyers.

           EARLY DREAMERS
                                         The dream of making a 
computer imitate us began many centuries ago. . . . 

                                                    The Greeks
                                         The hope of making an 
inanimate object act like a person can be traced back to the 
ancient Greeks. According to Greek mythology, Pygmalion sculpted 
a statue of a woman, fell in love with it, and prayed to the gods 
to make it come to life. His wish was granted ___ she came to 
life. And they lived happily ever after.

                                              Ramon Lull (1272 A.D.)
                                         In 1272 A.D. on the 
Spanish island of Majorca, Ramon Lull invented the idea of a 
machine that would produce all knowledge, by putting together 
words at random. He even tried to build it.
                                         Needless to say, he was 
a bit of a nut. Here's a description of his personality (written 
by Jerry Rosenberg, abridged):
                                         Ramon Lull married young 
and fathered two children ___ which didn't stop him from his 
courtier's adventures. He had an especially strong passion for 
married women. One day as he was riding his horse down the center 
of town, he saw a familiar woman entering church for a High Mass. 
Undisturbed by this circumstance, he galloped his horse into the 
cathedral and was quickly thrown out by the congregants. The lady 
was so disturbed by his scene that she prepared a plan to end 
Lull's pursuit once and for all. She invited him to her boudoir, 
displayed the bosom that he had been praising in poems written 
for her, and showed him a cancerous breast. ``See, Ramon,'' she 
said, ``the foulness of this body that has won thy affection! How 
much better hadst thou done to have set thy love on Jesus Christ, 
of Whom thou mayest have a prize that is eternal!''
                                         In shame Lull withdrew 
from court life. On four different occasions a vision of Christ 
hanging on the Cross came to him, and in penitence Lull became a 
dedicated Christian. His conversion was followed by a pathetic 
impulse to try to convert the entire Moslem world to 
Christianity. This obsession dominated the remainder of his life. 
His ``Book of Contemplation'' was divided into 5 books in honor 
of the 5 wounds of Christ. It contained 40 subdivisions ___ for 
the 40 days that Christ spent in the wilderness; 366 chapters ___ 
one to be read each day and the last chapter to be read only in a 
leap year. Each of the chapters had 10 paragraphs to commemorate 
the 10 commandments; each paragraph had 3 parts to signify the 
trinity ___ for a total of 30 parts a chapter, signifying the 30 
pieces of silver.
                                         In the final chapter of 
his book he tried to prove to infidels that Christianity was the 
only true faith.

  Gulliver's Travels Several centuries later ___ in 1726 ___ 
Lull's machine was pooh-poohed by Jonathan Swift, in Gulliver's 
Travels.
  Gulliver meets a professor who has built such a machine. The 
professor claims his machine lets ``the most ignorant person . . 
. write books in philosophy, poetry, politics, law, mathematics, 
and theology without the least assistance from genius and 
study.''
  The machine is huge ___ 20 feet on each side ___ and contains 
all the words of the language, in all their declensions, written 
on scraps of paper that are glued onto bits of wood connected by 
wires.
  Each of the professor's 40 students operates one of the 
machine's 40 cranks. At a given signal, every student turns his 
crank a random distance, to push the words into new positions.
  Gulliver says:
He then commanded 36 of the lads to read the several lines softly 
as they appeared upon the frame; and where they found three or 
four words together that might make part of a sentence, they 
dictated to the four remaining boys who were scribes. Six hours a 
day the young students were employed in this labor, and the 
professor showed me several volumes in large folio already 
collected, of broken sentences, which he intended to piece 
together, and out of those rich materials to give the world a 
complete body of all arts and sciences.

         Karel Capek (1920)
  The word robot was invented in 1920 by Karel Capek, a Czech 
playwright. His play ``R.U.R.'' shows a factory where the workers 
look human but are really machines. The workers are dubbed 
robots, because the Czech word for slave is robotnik.
  His play is pessimistic. The invention of robots causes 
unemployment. Men lose all ambition ___ even the ambition to 
raise children. The robots are used in war, go mad, revolt 
against mankind and destroy it. In the end only two robots are 
left. It's up to them to repopulate the world.

         Isaac Asimov (1942)
  Many sci-fi writers copied Capek's idea of robots, with even 
more pessimism. An exception was Isaac Asimov, who depicted 
robots as being loving. He coined the word robotics, which means 
the study of robots, and in 1942 developed what he calls the 
``Three Laws of Robotics''. Here's the version he published in 
1950:
  1. A robot may not injure a human being or, through inaction, 
allow a human being to come to harm.
  2. A robot must obey the orders given it by human beings, 
except where such orders would conflict with the First Law.
  3. A robot must protect its own existence, as long as such 
protection does not conflict with either the First or the Second 
Law.
                                               Norbert Wiener (1947)
                                         The word cybernetics was 
invented in 1947 by Norbert Wiener, an MIT professor. He defined 
it to be ``the science of control and communication in the animal 
and the machine.'' Wiener and his disciples, who called 
themselves cyberneticists, wondered whether it would be possible 
to make an electrical imitation of the human nervous system. It 
would be a ``thinking machine''. They created the concept of 
feedback: animals and machines both need to perceive the 
consequences of their actions, to learn how to improve 
themselves. For example, a machine that is producing parts in a 
factory should examine the parts it has produced, the heat it has 
generated, and other factors, to adjust itself accordingly.
                                         Wiener, like Ramon Lull, 
was something strange. He graduated from Tufts College when he 
was 14 years old, got his doctorate from Harvard when he was 18, 
and became the typical ``absent-minded professor''. Many 
anecdotes are told about him.
                                         For example, once he 
went to a conference and parked his car in the parking lot. When 
the conference was over, he went to the lot, but forgot where he 
parked his car, and even forgot what it looked like. So he waited 
until all the other cars were driven away, and took the car that 
was left.
                                         When he and his family 
moved to a new house a few blocks away, his wife gave him written 
directions on how to reach it, because she knew he was very 
absent-minded. But sure enough, when he was leaving his office at 
the end of the day, he couldn't remember where he put her note, 
and of course he couldn't remember where the new house was. So he 
drove to his old neighborhood instead. He saw a young child and 
asked her, ``Little girl, can you tell me where the Wieners have 
moved?'' ``Yes, Daddy,'' came the reply, ``Mommy said you'd 
probably be here, so she sent me to show you the way home.''
                                         One day he was sitting 
in the campus lounge, intensely studying a paper on the table. 
Every now and then, he would get up, pace a bit, and then return 
to the paper. Everyone was impressed by the enormous mental 
effort reflected on his face. Once again he rose from his paper, 
took a few rapid steps around the room, and collided with a 
student. The student said, ``Good afternoon, Professor Wiener.'' 
Wiener stopped, stared, clapped a hand to his forehead, said 
``Wiener ___ that's the word,'' and ran back to the table to fill 
the word ``wiener'' in the crossword puzzle he was working on.
                                         Once he drove 150 miles 
to a math conference at Yale University; but when the conference 
was over, he forgot he had come by car, so he returned by bus. 
The next morning, he went out to his garage to get his car, 
discovered it was missing, and complained to the police that 
while he was away someone had stolen it.
                                         Those anecdotes were 
collected by Howard Eves, a math historian.

                                                Alan Turing (1950)
                                         Can a computer 
``think''? In 1950, Alan Turing proposed the following test. In 
one room, put a human and a computer. In another room, put 
another human (called the Interrogator) and give him two 
terminals ___ one for communication with the computer, and the 
other for communication with the other human ___ but don't tell 
the Interrogator which terminal is which. If he can't tell the 
difference, the computer's doing a good job of imitating the 
human, and, according to Turing, we should say that the computer 
can ``think''.
  It's called the Imitation Game. The Interrogator asks 
questions. The human witness answers honestly. The computer 
pretends to be human.
  To win, the computer must be able to imitate human weaknesses 
as well as strengths. For example, when asking to add two 
numbers, it should pause before answering, as a human would. When 
asked to write a sonnet, a good imitation-human answer would be, 
``Count me out on this one. I never could write poetry.'' When 
asked ``Are you human'', the computer should say ``yes''.
  Such responses wouldn't be hard to program. But a clever 
Interrogator could give the computer a rough time, by requiring 
it to analyze its own thinking:
Interrogator:In the first line of your sonnet which reads ``Shall 
        I compare thee to a summer's day,'' wouldn't ``a spring 
        day'' do as well or better?
Witness:It wouldn't scan.

Interrogator:How about ``a winter's day''. That would scan all 
right.
Witness:Yes, but nobody wants to be compared to a winter's day.

Interrogator:Would you say Mr. Pickwick reminded you of 
Christmas?
Witness:In a way.

Interrogator:Yet Christmas is a winter's day, and I don't think 
        Mr. Pickwick would mind the comparison.
Witness:I don't think you're serious. By a winter's day one means 
        a typical winter's day, rather than a special one like 
        Christmas.
If the computer could answer questions that well, the 
Interrogator would have a hard time telling it wasn't human.
  Donald Fink has suggested that the Interrogator say, ``Suggest 
an unsolved problem and some methods for working toward its 
solution,'' and ``What methods would most likely prove fruitful 
in solving the following problem. . . . ''
  Turing believed computers would someday be able to win the game 
and therefore be considered to ``think''. In his article, he 
listed nine possible objections to his belief, and rebutted them. 
. . . 
  1. Soul Thinking's a function of man's immortal soul. Since 
computers don't have souls, computers can't think.
  Rebuttal: since God's all-powerful, He can give computers souls 
if He wishes. Just as we create children to house His souls, so 
should we serve Him by creating computers.
  2. Dreadful If machines could equal us in thinking, that would 
be dreadful!
  Rebuttal: too bad!
  3. Logicians Logicians have proved it's impossible to build a 
computer that can answer every question.
  Rebuttal: is it possible to find a human that can answer every 
question? Computers are no dumber than we. And though no one can 
answer every question, why not build a succession of computers, 
each one more powerful than the next, so every question could be 
answered by at least one of them?
  4. Conscious Although computers can produce, they can't be 
conscious of what they've produced. They can't feel pleasure at 
their successes, misery at their mistakes, and depression when 
they don't get what they want.
  Rebuttal: the only way to be absolutely sure whether a computer 
has feelings is to become one. A more practical experiment would 
be to build a computer that explains step-by-step its reasoning, 
its motivations, and the obstacles it is trying to overcome, and 
also analyzes emotional passages such as poetry. Such a computer 
is clearly not just parroting.
                                         5. Human A computer 
can't be kind, resourceful, beautiful, friendly, have initiative, 
have a sense of humor, tell right from wrong, make mistakes, fall 
in love, enjoy strawberries and cream, make someone fall in love 
with it, learn from experience, use words properly, be the 
subject of its own thought, have as much diversity of behavior as 
a man, or do something really new.
                                         Rebuttal: why not? 
Although such a computer hasn't been built yet, it might be 
possible in the future.
                                         6. Surprise The computer 
never does anything original or surprising. It does only what 
it's told.
                                         Rebuttal: how do you 
know ``original'' human work isn't just grown from a seed 
implanted by teaching, or the effect of well-known general 
principles? And who says computers aren't surprising? The 
computer's correct answers are often surprisingly different from 
a human's rough guesses.
                                         7. Binary Nerve cells 
can sense gradual increases in electrical activity ___ you can 
feel a ``little tingle'' or a ``mild pain'' or an ``ouch'' ___ 
whereas a computer's logic is only binary ___ either a ``yes'' or 
``no''.
                                         Rebuttal: by using 
techniques such as ``random numbers'', you can make the computer 
imitate the flexible, probabilistic behavior of the nervous 
system well enough so that the Interrogator can't tell the 
difference.
                                         8. Rules Life can't be 
reduced to rules. For example, if you have a traffic-light rule 
that says ``stop when the light is red, and go when the light is 
green'', what do you do when the light is broken, and both the 
red and green appear simultaneously? Maybe you should have an 
extra rule saying in that case to stop. But some further 
difficulty may arise with that rule, and you'd have to create 
another rule. And so on. You can't invent enough rules to handle 
all cases. Since computers must be fed rules, they cannot handle 
all of life.
                                         Rebuttal: although 
life's more than a simple set of rules, it might be the 
consequences of simple psychological laws of behavior, which the 
computer could be taught.
                                         9. ESP Humans have 
extrasensory perception (ESP), and computers don't.
                                         Rebuttal: maybe the 
computer's random-number generator could be hooked up to be 
affected by ESP. Or to prevent ESP from affecting the Imitation 
Game, put both the human witness and the computer in a 
telepathy-proof room.
                                         How to begin To make the 
computer an intelligent creature, Turing suggested two possible 
ways to begin. One way would be to teach the computer abstract 
skills, such as chess. The other way would be to give the 
computer eyes, ears, and other sense organs, teach it how to 
speak English, and then educate it the same way you'd educate a 
somewhat handicapped child.
                                         Suicide? Four years 
later ___ on June 8, 1954 ___ Turing was found dead in bed. 
According to the police, he died from potassium cyanide, 
self-administered. He'd been plating spoons with potassium 
cyanide in electrolysis experiments. His mother refuses to 
believe it was suicide, and hopes it was just an accident.

         UNDERSTAND ENGLISH
  It's hard to make the computer understand plain English!

              Confusion
  For example, suppose you feed the computer this famous saying:
Time flies like an arrow.
What does that saying mean? The computer might interpret it three 
ways. . . . 
Interpretation 1: the computer thinks ``time'' is a noun, so the 
sentence means ``The time can fly by as quickly as an arrow 
flies.''

Interpretation 2: the computer thinks ``time'' is a verb, so the 
sentence means ``Time the speed of flies like you'd time the 
speed of an arrow.''

Interpretation 3: the computer thinks ``time'' is an adjective, 
so the sentence means ``There's a special kind of insect, called 
a `time fly', and those flies are attracted to an arrow (in the 
same way moths are attracted to a flame).''
  Suppose a guy sits on a barstool and shares his drinks with a 
tall woman while they play poker for cash. If the woman says to 
him, ``Up yours!'', the computer might interpret it eight ways:
The woman is upset at what the man did.
The woman wants the man to raise up his glass, for a toast.
The woman wants the man to up the ante and raise his bet.
The woman wants the man to hold his cards higher, so she doesn't 
see them.
The woman wants the man to pick up the card she dealt him.
The woman wants the man to raise his stool, so she can see him 
eye-to-eye.
The woman wants the man to pull up his pants.
The woman wants the man to have an erection.
  For another example, suppose Mae West were to meet a 
human-looking robot and ask him:
Is that a pistol in your pocket, or are you glad to see me?
The robot would probably analyze that sentence too logically, 
then reply naively:
There is no pistol in my pocket, and I am glad to see you.
  In spite of those confusions, programmers have tried to make 
the computer understand English. Here are some famous attempts. . 
. . 

           Baseball (1961)
  In 1961 at MIT, programmers made the computer answer questions 
about baseball.
  In the computer's memory, they stored the month, day, place, 
teams, and scores of each game in the American League for one 
year. They programmed the computer so that you can type your 
question in ordinary English. The computer analyzes your 
question's grammar and prints the correct answer.
  Here are examples of questions the computer can analyze and 
answer correctly:
Who did the Red Sox lose to on July 5?
Who beat the Yankees on July 4?
How many games did the Yankees play in July?
Where did each team play in July?
In how many places did each team play in July?
Did every team play at least once in each park in each month?

                                         To get an answer, the 
computer turns your questions into equations:
Question                                                       
Equations
Where did the Red Sox play on July 7?                          
place = ?
                                                               te
am = Red Sox
                                                               mo
nth = July
                                                               da
y = 7

What teams won 10 games in July?                               
team (winning) = ?
                                                               ga
me (number of) = 10
                                                               mo
nth = July

On how many days in July did eight teams play?                 
day (number of) = ?
                                                               mo
nth = July
                                                               te
am (number of) = 8
                                         To do that, the computer 
uses this table:
Word in your question                                  Equation
where                                                  place = ?
Red Sox                                                team = Red 
Sox
July                                                   month = 
July
who                                                    team = ?
team                                                   team =
                                         The computer ignores 
words such as the, did, and play.
                                         If your question 
mentions Boston, you might mean either ``place = Boston'' or 
``team = Red Sox''. The computer analyzes your question to 
determine which equation to form.
                                         After forming the 
equations, the computer hunts through its memory, to find the 
games that solve the equations. If an equation says ``number 
of'', the computer counts. If an equation says ``winning'', the 
computer compares the scores of opposing teams.
                                         The programmers were 
Bert Green, Alice Wolf, Carol Chomsky, and Kenneth Laughery.

                                              What's a story problem?
                                         When you were in school, 
your teacher told you a story that ended with a mathematical 
question. For example:
Dick had 5 apples. He ate 3. How many are left?
                                         In that problem, the 
last word is: left. That means: subtract. So the correct answer 
is 5 minus 3, which is 2.
                                         Can the computer solve 
problems like that? Here's the most famous attempt. . . . 
           Arithmetic & algebra (1964)
  MIT awarded a Ph.D. to Daniel Bobrow, for programming the 
computer to solve story problems involving arithmetic and 
algebra.
  Customers Let's see how the computer solves this problem:
If the number of customers Tom gets is twice the square of 20 
percent of the number of advertisements he runs, and the number 
of advertisements he runs is 45, what is the number of customers 
Tom gets?
  To begin, the computer replaces twice by 2 times, and replaces 
square of by square.
  Then the computer separates the sentence into smaller 
sentences:
The number of customers Tom gets is 2 times the square 20 percent 
of the number of advertisements he runs. The number of 
advertisements he runs is 45. What is the number of customers Tom 
gets?
  The computer turns each sentence into an equation:
number of customers Tom gets = 2 * (.20 * number of 
advertisements he runs)^2
number of advertisements he runs = 45
X = number of customers Tom gets
  The computer solves the equations and prints the answer as a 
complete sentence:
The number of customers Tom gets is 162.
  Here's a harder problem:
The sum of Lois's share of some money and Bob's share is $4.50. 
Lois's share is twice Bob's. Find Bob's and Lois's share.
  Applying the same method, the computer turns the problem into 
these equations:
Lois's share of some money + Bob's share = 4.50 dollars
Lois's share = 2 * Bob's
X = Bob's
Y = Lois's share
  The computer tries to solve the equations but fails. So it 
assumes ``Lois's share'' is the same as ``Lois's share of some 
money'', and ``Bob's'' is the same as ``Bob's share''. Now it has 
six equations:
Original equations
Lois's share of some money + Bob's share = 4.50 dollars
Lois's share = 2 * Bob's
X = Bob's
Y = Lois's share

Assumptions
Lois's share = Lois's share of some money
Bob's = Bob's share
  It solves them and prints:
Bob's is 1.50 dollars.
Lois's share is 3 dollars.
  Distance The computer can solve problems about distance:
The distance from New York to Los Angeles is 3000 miles. If the 
average speed of a jet plane is 600 miles per hour, find the time 
it takes to travel from New York to Los Angeles by jet.
  The resulting equations are:
distance from New York to Los Angeles = 3000 * miles
average speed of jet plane = (600 * miles)/(1 * hours)
X = time it takes to travel from New York to Los Angeles by jet
  The computer is unable to solve them. But in its memory it 
finds the formula ``distance = speed * time''. It winds up with 7 
equations:
Original equations
distance from New York to Los Angeles = 3000 * miles
average speed of jet plane = (600 * miles)/(1 * hours)
X = time it takes to travel from New York to Los Angeles by jet

Formula
distance = speed * time

Assumptions
distance = distance from New York to Los Angeles
speed = average speed of jet plane
time = time it takes to travel from New York to Los Angeles by 
jet
  It solves them and prints:
The time it takes to travel from New York to Los Angeles by jet 
is 5 hours.
                                                     Age The 
computer can solve problems about age:
Mary is twice as old as Ann was when Mary was as old as Ann is 
now. If Mary is 24 years old, how old is Ann?
                                                     To begin, 
the computer replaces twice by 2 times, and replaces how old by 
what.
                                                     When the 
computer sees the words as old as, it knows the problem has to do 
with ages, so it breaks the problem into these sentences:
Mary's age is 2 times Ann's age X years ago. X years ago Mary's 
age is Ann's age now. Mary's age is 24. What is Ann's age?
The resulting equations are:
Mary's age = 2 * (Ann's age - X)
Mary's age - X = Ann's age
Mary's age = 24
Y = Ann's age
                                                     The computer 
prints:
Ann's age is 18.
                                                     Hint If a 
situation appears hopeless, the computer asks you for help. In 
the following conversation, the human poses a problem, and the 
computer begs for a hint:
Human:                                                   The 
                                                         gross 
                                                         weight 
                                                         of a 
                                                         ship is 
                                                         20000 
                                                         tons. If 
                                                         its net 
                                                         weight 
                                                         is 15000 
                                                         tons, 
                                                         what is 
                                                         the 
                                                         weight 
                                                         of the 
                                                         ship's 
                                                         cargo?
Computer:                                                Do you 
                                                         know any 
                                                         more 
                                                         relation
                                                         ships 
                                                         among 
                                                         these 
                                                         variable
                                                         s: gross 
                                                         weight 
                                                         of ship, 
                                                         tons, 
                                                         its net 
                                                         weight, 
                                                         weight 
                                                         of 
                                                         ship's 
                                                         cargo?

Human:                                                   Yes.
Computer:                                                Tell me.

Human:                                                   The 
                                                         weight 
                                                         of a 
                                                         ship's 
                                                         cargo is 
                                                         the 
                                                         differen
                                                         ce 
                                                         between 
                                                         the 
                                                         gross 
                                                         weight 
                                                         and the 
                                                         net 
                                                         weight.
Computer:                                                The 
                                                         weight 
                                                         of the 
                                                         ship's 
                                                         cargo is 
                                                         5000 
                                                         tons.
                                                     Limitations 
The program has some limitations. It cannot solve quadratic 
equations. If the computer tries to apply the formula ``distance 
= speed * time'' to a problem involving two distances, it forgets 
which distance is which.
                                                     The 
computer's vocabulary is limited. It doesn't realize that how 
many means what is the number of, and how far is means what is 
the distance to. For problems about age, the characters must be 
named Mary, Ann, Bill, Father, or Uncle, unless you diddle with 
the computer's memory.
                                                     If the human 
types Tom has 2 apples, 3 bananas, and 4 pears, the comma before 
the and makes the computer split the sentence into two wrong 
``sentences'':
Tom has 2 apples, 3 bananas.
4 pears.

  If the human mentions the number of times John went to the 
movies, the computer thinks times means multiplication, and tries 
to multiply number of by John went to the movies.

      Enclyclopedia (1964-1966)
  In 1964, Simmons, Klein, and McConlogue (at the Systems 
Development Corporation) fed a child's encyclopedia into a 
computer.
  If you type What do worms eat? the computer hunts through the 
encyclopedia, to find sentences mentioning both worms and eat. 
(To hasten the hunt, it uses an index produced by another 
program.) It finds two sentences:
Birds eat worms on the grass.
Most worms usually eat grass.
  After analyzing the grammar of your question and those 
sentences, the computer realizes the first sentence is 
irrelevant, and prints just the correct answer:
Most worms usually eat grass.
  In 1965, the program's abilities were extended, so that if you 
type What animals live longer than men? the computer searches 
through the encyclopedia for related words:
Word in sentenceRelated words searched
animals     mammals, reptiles, fish
live        age
longer      older, ancient
men         person, people, women
  Here's an example of the program's operation in 1966. The human 
creates some encyclopedia material about horses, and then 
retrieves it:
Human:Enter horse=noun, is=isverb, animal=noun, live=verb, 
      on=prep, farm=noun, strong=adj, pull=verb, wagon=noun, 
      most=adj, are=isverb, eat=verb, hay=noun, all=adj, red=adj, 
      many=adj, have=haveverb, long=adj, mane=noun, some=adj, 
      person=noun, race=verb.
Computer:Entered in dictionary.

Human:Plurals horse=horses, animal=animals, farm=farms, 
      wagon=wagons, mane=manes, person=people.
Computer:Ok.

Human:Start.
Computer:Ready.

Human:A horse is an animal. Horses live on a farm. Strong horses 
      pull wagons. Most horses are strong. Horses eat hay. All 
      horses are red. Many horses have long manes. Some people 
      race horses.
Computer:Learned.

Human:Forget ``all horses are red''.
Computer:Forgotten.

Human:What is a horse?
Computer:Horse is an animal.

Human:What do horses eat?
Computer:Horses eat hay.

Human:What do horses do?
Computer:Horses live on a farm and eat hay. Strong horses pull 
wagons.

Human:What do strong horses do?
Computer:Strong horses pull wagons.

Human:Do many horses have long manes?
Computer:Yes.

Human:Do all horses have long manes?
Computer:To my knowledge, no.

Human:Describe horses?
Computer:Horses are an animal. Most horses are strong. Many 
      horses have long manes. Horses live on a farm and eat hay. 
      Strong horses pull wagons. Some people race horses.

                                         When the computer's 
answer consists of several sentences, it prints the most relevant 
sentence first, and the others in decreasing order of relevance.

                                                  Military (1966)
                                         Thompson and Craig (at 
General Electric) made the computer answer military questions 
such as:
Has the 25th battalion arrived in Texas since 3 P.M.?

Is the 100th scheduled to arrive at Ft. Lewis before the 200th 
leaves Ft. Lewis?

                                                 Eliza (1966-1967)
                                         In 1966 at MIT, Joseph 
Weizenbaum wrote the Eliza program, which makes the computer act 
as a psychotherapist.
                                         In 1967, he changed the 
program, to make it handle keywords such as also, call, compute, 
define, is, let, of, thanks, where, and the symbol =.
                                         In the following 
conversation, the human teaches the computer how to find the area 
of a circle, a sphere, and a square, and then asks the computer 
questions about geometry. The human also teaches the computer how 
to speak German ___ 
English                                      German
I say                                        ich sage
I mean                                       meine ich
what is                                      wieviel ist
squared                                      quadrat
and gradually starts speaking to the computer in German.
Human:                                       The area of a circle 
                                             is pi times the 
                                             radius of the circle 
                                             squared. The area of 
                                             a sphere is pi times 
                                             the diameter of the 
                                             sphere squared. The 
                                             area of a square is 
                                             the side of the 
                                             square squared. The 
                                             diameter of an 
                                             object is twice the 
                                             radius of the 
                                             object. The radius 
                                             of a ball is 10. 
                                             What is the area of 
                                             the ball?
Computer:                                    The assumption that 
                                             ball is circle is 
                                             consistent ___ shall 
                                             I go on?

Human:                                       No.
Computer:                                    The assumption that 
                                             ball is sphere and 
                                             object is consistent 
                                             ___ shall I go on?

Human:                                       Yes.
Computer:                                    It's 1256.6359.

Human:                                       What is the diameter 
of the ball?
Computer:                                    It's 20.

Human:                                       The radius of a dish 
is 10. What's the area of the dish?
Computer:                                    The assumption that 
dish is circle is consistent ___ shall I go on?

Human:                                       Yes.
Computer:                                    It's 314.15899.

Human:                                       The radius of a 
                                             globe is 10. A globe 
                                             is a sphere. A 
                                             sphere is an object. 
                                             What is the area of 
                                             the globe?
Computer:                                    It's 1256.6359.

Human:                                       The side of a plate 
is 10. What is the area of the plate?
Computer:                                    The assumption that 
                                             plate is square is 
                                             consistent ___ shall 
                                             I go on?

Human:                                       Yes.
Computer:                                    It's 100.

Human:                                       When I say board I 
                                             mean plate. What is 
                                             3 times the side of 
                                             the board?
Computer:                                    It's 30.

Human:                                       Please call that x. 
Let f(z) be z squared minus z. Compute f(x).
Computer:                                    It's 870.

Human:                                       When I say ich sage 
                                             I mean I say. When 
                                             ich sage meine ich I 
                                             mean I mean. Wenn 
                                             ich sage wieviel ist 
                                             meine ich what is. 
                                             Wenn ich sage 
                                             quadrat meine ich 
                                             squared. Nun, sagen 
                                             sie mir bitte, 
                                             wieviel is x 
                                             quadrat.
Computer:                                    I didn't understand 
you.

Human:                                       Ja, tut mir leid, 
ich sollte fragen wieviel IST x quadrat.
Computer:                                    It's 900.

           Calculus (1969)
  At MIT, Charniak made the computer solve story problems 
involving calculus.
Human:Water is flowing into a conical filter at the rate of 15 
      cubic inches per second. If the radius of the base of the 
      filter is 5 inches and the altitude is 10 inches, find the 
      rate at which the water level is rising when the volume is 
      100 cubic inches.
Computer:The answer is .53132943 * in * sec^-1 * pi^-.33333332.

         Probability (1971)
  Rensselaer Polytechnic Institute awarded a Ph.D. to J.P. Gelb, 
for making the computer solve story problems involving 
probability.
Human:From a zorch containing 4 ferd and 3 brakky and 5 
      chartreuse werfels, 3 are drawn. What is the probability 
      that 2 are chartreuse and the other brakky?
Computer:Replacement involved?

Human:No.
Computer:3/22 (or .1363636).


         SURVEYING THE FIELD
                                         The field of 
``artificial intelligence'' includes many categories.
                                         For example, it includes 
attempts to make the computer win at chess and checkers, 
understand English, and create its own original art and music. It 
also includes attempts to imitate human feelings, personal 
interactions, and therapists. I explained those topics earlier.

                                                  Protocol method
                                         During the 1950's and 
1960's, most research in artificial intelligence was done at the 
Massachusetts Institute of Technology (MIT) and the Carnegie 
Institute of Technology (CIT, now called Carnegie-Mellon 
University). At Carnegie, the big names were Allen Newell and 
Herbert Simon. They invented the protocol method. In the protocol 
method, a human is told to solve a tough problem and, while he's 
solving it, to say at each moment what he's thinking. A 
transcript of his train of thought is recorded and called the 
protocol. Then programmers try to make the computer imitate that 
train of thought.
                                         Using the protocol 
method, Newell and Simon produced programs that could ``think 
like humans''. The thinking, like human thinking, was imperfect. 
Their research did not try to make the computer a perfect 
thinker; instead, it tried to gain insight into how humans think. 
Their point of view was: if you think you really understand human 
psychology, go try to program it. Their attempt to reduce human 
psychology to computer programs is called mentalism, and has 
replaced Skinner's stimulus-response behaviorism as the dominant 
force in psychology today.

                                                   Abstract math
                                         Many programmers have 
tried to make the computer do abstract math.
                                         In 1957 Newell, Simon, 
and Shaw used the protocol method to make the computer prove 
theorems about symbolic logic, such as ``Not (p or q) implies not 
p''. In 1959 and 1960, Herbert Gelernter and his friends made the 
computer prove theorems about Euclidean geometry, such as ``If 
the segment joining the midpoints of the diagonals of a trapezoid 
is extended to intersect a side of the trapezoid, it bisects that 
side.''
                                         In 1961, MIT awarded a 
Ph.D. to James Slagle for making the computer compute indefinite 
integrals, such as:
       4
     x    
            dx
     2 5/2
  (1-x )
The computer gets the answer, which is:
              3
           tan  arcsin x
arcsin x +               - tan arcsin x + c
                 3
                                         Each of those programs 
works by drawing a tree inside the computer's memory. Each branch 
of the tree represents a possible line of attack. The computer 
considers each branch and chooses the one that looks most 
promising.
                                         A better symbolic-logic 
program was written by Hao Wang in 1960. His program doesn't need 
trees; it always picks the right attack immediately. It's 
guaranteed to prove any theorem you hand it, whereas the program 
by Newell, Simon, and Shaw got stuck on some hard ones.
  A better indefinite integration program was written by Joel 
Moses in 1967 and further improved in 1969. It uses trees very 
rarely, and solves almost any integration problem.
  A program that usually finds the right answer but might fail on 
hard problems is called heuristic. A heuristic program usually 
involves trees. The checkers, chess, and geometry programs are 
heuristic. A program that's guaranteed to always give the correct 
answer is called algorithmic. The original symbolic-logic program 
was heuristic, but Wang's improvement is algorithmic; Moses's 
indefinite integration program is almost algorithmic.

                       GPS
  In 1957 Newell, Simon, and Shaw began writing a single program 
to solve all problems. They called the program GPS (General 
Problem Solver). If you feed the program a goal, a list of 
operators, and associated information, the program will tell you 
how to achieve the goal by using the operators.
  For example, suppose you want the computer to solve this simple 
problem: a monkey would like to eat some bananas that are too 
high for him to reach, but there's a box nearby he can stand on. 
How can he get the bananas?
  Feed the GPS program this information. . . . 
Now:  monkey's place = place#1; box's place = place#2; contents 
of monkey's hand = empty

Want: contents of monkey's hand = the bananas

Difficulties:contents of monkey's hand is harder to change than 
      box's place, which is harder to change than monkey's place

Allowable operatorDefinition
climb box     before:monkey's place = box's place
              after:monkey's place = on the box

walk to x     after:monkey's place = x

move box to x before:monkey's place = box's place
              after:monkey's place = x; box's place = x

get bananas   before:box's place = under the bananas; monkey's 
place = on the box
              after:contents of monkey's hand = the bananas
  GPS will print the solution:
walk to place#2
move box to under the bananas
climb box
get bananas
  The GPS approach to solving problems is called means-ends 
analysis: you tell the program the means (operators) and the end 
(goal). The program has proved theorems in symbolic logic, 
computed indefinite integrals, and solved many famous puzzles, 
such as ``The Missionaries and the Cannibals'', ``The Tower of 
Hanoi'', and ``The 5-Gallon Jug and the 8-Gallon Jug''. But the 
program works slowly, and you must feed it lots of information 
about the problem. The project was abandoned in 1967.

                     Vision
  Another large topic in artificial intelligence is computer 
vision: making the computer see.
  The first problem tackled was pattern recognition: making the 
computer read handwritten printed letters. The problem is hard, 
because some people make their letters very tall or wide or 
slanted or curled or close together, and the pen may skip. 
Reasonably successful programs were written, although computers 
still can't tackle script.
  Interest later shifted to picture processing: given a 
photograph of an object, make the computer tell what the object 
is. The problem is hard, because the photo may be taken from an 
unusual angle and be blurred, and because the computer gets 
confused by shadows.
  Scene analysis is even harder: given a picture of a group of 
objects, make the computer tell which object is which. The 
problem is hard, because some of the objects may be partly hidden 
behind others, and because a line can have two different 
interpretations: it can be a crease in one object, or a 
dividing-line between two objects.
  Most of the research in picture processing and scene analysis 
was done from 1968 to 1972.
                                                     Ray Kurzweil 
has invented an amazing machine whose camera looks at a book and 
reads the book, by using a voice synthesizer. Many blind people 
use it.

                                                            Robots
                                                     Researchers 
have built robots. The first robots were just for experimental 
fun, but today's robots are truly useful: for example, the 
Japanese are using robots to manufacture cars. In the United 
States, many young kids are being taught ``LOGO'', which is a 
language developed at the MIT Artificial Intelligence Laboratory 
that makes the computer control a robot turtle.

                                                       Today's research
                                                     Today, 
research in artificial intelligence is done at four major 
universities: MIT, Carnegie, Stanford, and Edinburgh (Scotland).
          Reflexive control
  In the Soviet Union, weird researchers have studied reflexive 
control: they programmed the computer to be disobedient. The 
first such programmer was Lefevr, in 1967. In 1969 Baranov and 
Trudolyubov extended his work, by making the computer win this 
disobedience game:
The human begins by choosing either node 9 or node 26, but 
doesn't tell the computer which node he's chosen. The computer 
starts at node 12; on each turn, it moves to an adjacent node. 
When it reaches either node 9 or node 26, the game ends: if the 
node the computer reaches is one of the human chose, the human 
wins; if the computer reaches the opposite node, the computer 
wins. Before each move, the human tells the computer where to go; 
but the computer may decide to do the opposite (disobey).
  What strategy should the computer use? If it always obeys, or 
always disobeys the human will catch on and make it lose.
  Instead, Baranov and Trudolyubov programmed the computer to 
react as follows:
obey the human twice, then disobey three times, then obey once, 
disobey thrice, obey once, disobey twice, obey thrice, disobey 
once, obey thrice, disobey once, . . . 
The irregular alternation of obedience and disobedience confuses 
the human in a way that works to the computer's advantage. Using 
that strategy, the computer played against 61 humans, and won 
against 44 of them (72%). In other words, the typical human tried 
to mislead the computer but in fact ``clued it in'' to the 
human's goal.
  Later experiments with other games indicated that the following 
pattern of disobedience is usually more effective:
obey the human twice, disobey thrice, obey once, disobey four 
times, obey once, disobey thrice, obey thrice, disobey twice, 
obey thrice, disobey once, obey once, disobey once

                                                  Misinformation
                                         Unfortunately, most 
research in the field of artificial intelligence is just a lot of 
hot air. For years, researchers have been promising that 
intelligent, easy-to-use English-speaking computers and robots 
would be available at low prices ``any day now''. After several 
decades of listening to such hoopla, I've given up waiting. The 
field of artificial intelligence should be renamed ``artificial 
optimism''.
                                         Whenever a researcher in 
the field of artificial intelligence promises you something, 
don't believe it until you see it and use it personally, so you 
can evaluate its limitations.
                                         If a computer seems to 
give intelligent replies to English questions posed by a salesman 
or researcher demonstrating artificial intelligence, try to 
interrupt the demo and ask the computer your English questions. 
You'll typically find that the computer doesn't understand what 
you're talking about at all: the demo was a cheap trick that 
works just with the peculiar English questions asked by the 
demonstrator.
                                         For many years, the top 
researchers in artificial intelligence have been exaggerating 
their achievements and underestimating how long it will take to 
develop a truly intelligent computer. Let's look at their history 
of lies. . . . 
                                         In 1957 Herbert Simon 
said, ``Within ten years a digital computer will be the world's 
chess champion.'' In 1967, when the ten years had elapsed, the 
only decent chess program was Greenblatt's, which the American 
Chess Federation rated ``class D'' (which means ``poor''). Though 
chess programs have improved since then, the best chess program 
is still far less than an  ``international master'' or 
``grandmaster'' or ``world champion''.
                                         In 1957 Simon also said, 
``Within ten years a digital computer will discover and prove an 
important new mathematical theorem.'' He was wrong. The computer 
still hasn't discovered or proved any important new mathematical 
theorem. The closest call came in 1976, when it did the 
non-abstract part of the proof of the ``4-color theorem''.
                                         In 1958 Newell, Simon, 
and Shaw wrote a chess-playing program which they admitted was 
``not fully debugged'' so that one ``cannot say very much about 
the behavior of the program''; but they claimed it was ``good in 
spots (opening)''. In 1959 the founder of cybernetics, Norbert 
Wiener, exaggerated about their program; he told New York 
University's Institute of Philosophy that ``chess-playing 
machines as of now will counter the moves of a master player with 
the moves recognized as right in the textbooks, up to some point 
in the middle game.'' In the same symposium Michael Scriven 
carried the exaggeration even further by saying, ``Machines are 
already capable of a good game.'' In fact, the program they were 
describing played very poorly, and in its last official bout 
(October 1960) was beaten by a ten-year-old kid who was a novice.
                                         In 1960 Herbert 
Gelernter (who wrote the geometry-theorem program) said, ``Today 
hardly an expert will contest the assertion that machines will be 
proving interesting theorems in number theory three years 
hence.'' More than twenty years have elapsed since then, but 
neither Gelernter nor anyone else has programmed the computer to 
prove theorems in number theory.
  In June 1963 this article appeared in the Chicago Tribune:
The development of a machine that can listen to any conversation 
and type out the remarks just like an office secretary was 
announced yesterday by a Cornell University expert on learning 
machines. The device is expected to be in operation by fall. 
Frank Rosenblatt, director of Cornell's cognitive systems 
research, said the machine will be the largest ``thinking'' 
device built to date. Rosenblatt made his announcement at a 
meeting on learning machines at Northwestern University's 
Technological Institute.
No such machine exists today, let alone in 1963.
  Also in 1963, W. Ross Ashby said, ``Gelernter's theorem-proving 
program has discovered a new proof of the pons asinorum that 
demands no construction.'' He said the proof is one that ``the 
greatest mathematicians of 2000 years have failed to notice . . . 
which would have evoked the highest praise had it occurred.'' In 
fact, the pons asinorum is just the simple theorem that the 
opposite angles of an isosceles triangle are equal, and the 
computer's constructionless proof had already been discovered by 
Pappus in 300 A.D.
  In 1968 the head of artificial intelligence in Great Britain, 
Donald Michie, said, ``Today machines can play chess at 
championship level.'' In fact, when computers were allowed to 
participate in human chess tournaments, they almost always lost.
  In 1970 the head of artificial intelligence at MIT, Marvin 
Minsky, said:
In three to eight years we will have a machine with the general 
intelligence of an average human being. I mean a machine that 
will be able to read Shakespeare, grease a car, play office 
politics, tell a joke, have a fight. At that point, the machine 
will begin to educate itself with fantastic speed. In a few 
months it will be at genius level, and a few months after that 
its powers will be incalculable.
His prediction that it would happen in three to eight years ___ 
between 1973 and 1978 ___ was ridiculous. I doubt it will happen 
during this century, if ever.
  Exaggerations concern not just the present and future but also 
the past. Back in 1962 Arthur Samuel's checker program won one 
game against Robert Nealey, ``a former Connecticut checkers 
champion''. Notice that Nealey was a former champion, not the 
current champion when the game was played. Also notice the 
program won a single game, not a match; and in fact it lost to 
Nealey later. In 1971 James Slagle slid over those niceties, when 
he just said that the program ``once beat the champion of 
Connecticut.'' More recent writers, reading Slagle's words, have 
gone a step further and omitted the word once: one textbook says, 
``The current program beat the champion of Connecticut''. It's 
not true.
  Why do leaders of artificial intelligence consistently 
exaggerate? The answer is obvious: to get more research funds 
from the government. Hubert Dreyfus, chairman of the philosophy 
department at Berkeley, annoys them by attacking their claims.
                                                     The brain
                                         Will the computer be 
able to imitate the human brain? Opinions vary.
                                         Marvin Minsky, head of 
artificial intelligence at MIT, says yes: ``After all, the human 
brain is just a computer that happens to be made out of meat.''
                                         Biologists argue no: the 
brain is composed of 12 billion neurons, each of which has 
between 5,000 and 60,000 dendrites for input and a similar number 
of axons for output; the neurons act in peculiar ways, and no 
computer could imitate all that with complete accuracy ___ ``The 
neuron is qualitatively quite different from on-off components of 
current computers.''
                                         Herbert Simon (head of 
artificial intelligence at Carnegie and a psychologist), points 
out that certain aspects of the brain, such as short-term memory, 
are known to have very limited capacity and ability. He believes 
the inner workings of the brain are reasonably simple; it 
produces complicated output only because it receives complicated 
input from the sense organs and environment: ``A man, viewed as a 
behaving system, is quite simple. The apparent complexity of his 
behavior over time is largely a reflection of the complexity of 
the environment in which he finds himself.'' Simon believes that 
if a computer were given good sense organs, the ability to move, 
and an elementary ability to learn, and were placed in a 
stimulating environment (unlike the dull four walls of a computer 
center), it would start acting in complex ways also.
                                         Hubert Dreyfus, chairman 
of the philosophy department at Berkeley, argues that progress in 
artificial intelligence has been very small, is being blocked now 
by impenetrable barriers, and ___ most important ___ the 
computer's approach to solving problems bears little relationship 
to the more powerful methods used by humans. He's cynical about 
the claim that an improvement in computer programs represents 
progress toward understanding the human mind, which is altogether 
different: ``According to this definition, the first man to climb 
a tree could claim tangible progress toward reaching the moon. 
Rather than climbing blindly, it's better to look where one is 
going.''