Artificial Intelligence,
Natural Language,
and the Chinese Room
William J. Rapaport
Department of Computer Science & Engineering,
Department of Philosophy, Department of Linguistics,
and Center for Cognitive Science
rapaport@buffalo.edu
http://www.cse.buffalo.edu/~rapaport
What Is AI?
1. “The science of making machines do things that
would require intelligence if done by humans.”
–
–
Marvin Minsky
Using humans to tell us how to program computers
•
•
–
e.g., play chess, solve calculus problems, …
e.g., see, use language, …
“classical AI”
What Is AI? (continued)
2. “The use of computer programs and
programming techniques to cast light on the
principles of intelligence in general
and human thought in particular.”
–
–
–
Margaret Boden
Using computers to tell us something about humans.
Cognitive science
What Is AI? (cont’d)
• Can computers think?
• Is thinking computable?
– E.g., is natural-language understanding computable?
– In general: Is “cognition” computable?
• If so:
– how can we program computers to do it?
– how will we know when we’ve succeeded?
• one possible answer: The Turing Test
Alan Turing
• British, 1912-1954
• “invented” the idea of
computation
– Turing “machine”
• cracked the Nazi
“Enigma” code
during WW II
• devised test for AI:
– Turing “test”
Turing Machine
• Everything that is computable can be computed using:
– a machine with:
• an infinite tape divided into squares (with ‘0’ on each)
• a movable read-write head
– a programming language with only:
• 2 nouns: 0, 1
• 2 verbs: move(left or right), print(0 or 1)
• 3 grammar rules:
– sequence (begin do this; then do that end)
» where “this”/“that” = print, move, or any grammatical instruction
– selection (if current square=0 then do this else do that)
– repetition (while current square=0 [or: current square=1] do this)
• Not everything can be computed!
– “halting problem”: can’t always detect infinite loops
– can cognition be computed?
How Computers Can Think
• If (human) cognition is computable,
then (human) cognitive states & processes
can be expressed as algorithms
• If cognitive states & process
can be expressed as algorithms,
then they can be implemented
on non-human computers
How Computers Can Think (cont’d)
• Are computers executing such cognitive algorithms
merely simulating cognitive states & processes?
• Or are they actually exhibiting them?
– Do such computers think?
• Answer: Turing’s Test
Objection: Searle’s Chinese-Room Argument
My reply: Computers can understand just by
manipulating symbols
(like a Turing machine)
The Imitation Game
MAN
WOMAN
“I’m the woman”
“I’m the woman”
INTERROGATOR
The Turing Test
The Imitation Game
COMPUTER
MAN
WOMAN
“I’m the woman”
“I’m the woman”
INTERROGATOR
The Turing Test #2
The Imitation Game
COMPUTER
MAN
MAN
WOMAN
“I’m the woman”
man
“I’m the woman”
man
INTERROGATOR
The Turing Test #3
The Imitation Game
COMPUTER
MAN
HUMAN
WOMAN
“I’m the woman”
human
“I’m the woman”
human
INTERROGATOR
The Turing Test
I
Questions
Responses
H? / C?
“I believe that at the end of the century the use of words
and general educated opinion will have altered so much
that one will be able to speak of machines thinking
without expecting to be contradicted.”
- Turing 1950
Thinking vs. “Thinking”
© The New Yorker, 5 July 1993
Thinking vs. “Thinking”, cont’d.
• Cartoon works because:
– You don’t know whom you’re communicating with via computer
• Nevertheless, we assume we are talking to a human
– I.e., entity with human cognitive capacities
= Turing’s point, namely:
• Argument from Analogy:
– Solution to Problem of Other Minds
= I know I think; how do I know you do?
– You are otherwise like me
 (probably) you are like me w.r.t. thinking
What Is a Computer?
The Chinese Room
© MacroVU Press
The Chinese-Room Argument
• It’s possible to pass TT, yet not (really) think
story + questions
I
(in Chinese)
(native Chinese
speaker)
responses
(in fluent Chinese)
H
(who can’t
understand Ch.)
+
(Eng.) program
for manipulating
[Ch.] “squiggles”
Searle’s Chinese-Room Argument
(s1) Computer programs just manipulate symbols
(s2) Understanding has to do with meaning
(s3) Symbol manipulation alone is not sufficient
for meaning
(s4)  No computer program can understand
¬ (s3): You can understand just by
manipulating symbols!
Contextual Vocabulary
Acquisition
• Could Searle-in-the-room figure out a
meaning for an unknown squiggle?
• Yes!
– Same way you can figure out a meaning
for an unfamiliar word from context
What Does ‘Brachet’ Mean?
(From Malory’s Morte D’Arthur [page # in brackets])
1.
2.
3.
4.
10.
18.
There came a white hart running into the hall with a white brachet
next to him, and thirty couples of black hounds came running after
them. [66]
As the hart went by the sideboard,
the white brachet bit him. [66]
The knight arose, took up the brachet and
rode away with the brachet. [66]
A lady came in and cried aloud to King Arthur,
“Sire, the brachet is mine”. [66]
There was the white brachet which bayed at him fast. [72]
The hart lay dead; a brachet was biting on his throat,
and other hounds came behind. [86]
Cassie learns what “brachet” means:
Background info about: harts, animals, King Arthur, etc.
No info about:
brachets
Input:
formal-language (SNePS) version of simplified English
A hart runs into King Arthur’s hall.
• In the story, B12 is a hart.
• In the story, B13 is a hall.
• In the story, B13 is King Arthur’s.
• In the story, B12 runs into B13.
A white brachet is next to the hart.
• In the story, B14 is a brachet.
• In the story, B14 has the property “white”.
• Therefore, brachets are physical objects.
(deduced while reading;
PK: Cassie believes that only physical objects have color)
--> (defineNoun "brachet")
Definition of brachet:
Class Inclusions: phys obj,
Possible Properties: white,
Possibly Similar Items:
animal, mammal, deer,
horse, pony, dog,
I.e., a brachet is a physical object that can be white
and that might be like an animal, mammal, deer,
horse, pony, or dog
A hart runs into King Arthur’s hall.
A white brachet is next to the hart.
The brachet bites the hart’s buttock.
[PK: Only animals bite]
--> (defineNoun "brachet")
Definition of brachet:
Class Inclusions: animal,
Possible Actions: bite buttock,
Possible Properties: white,
Possibly Similar Items: mammal, pony,
A hart runs into King Arthur’s hall.
A white brachet is next to the hart.
The brachet bites the hart’s buttock.
The knight picks up the brachet.
The knight carries the brachet.
[PK: Only small things can be picked up/carried]
--> (defineNoun "brachet")
Definition of brachet:
Class Inclusions: animal,
Possible Actions: bite buttock,
Possible Properties: small, white,
Possibly Similar Items: mammal, pony,
A hart runs into King Arthur’s hall.
A white brachet is next to the hart.
The brachet bites the hart’s buttock.
The knight picks up the brachet.
The knight carries the brachet.
The lady says that she wants the brachet.
[PK:
Only valuable things are wanted]
--> (defineNoun "brachet")
Definition of brachet:
Class Inclusions: animal,
Possible Actions: bite buttock,
Possible Properties: valuable, small,
white,
Possibly Similar Items: mammal, pony,
A hart runs into King Arthur’s hall.
A white brachet is next to the hart.
The brachet bites the hart’s buttock.
The knight picks up the brachet.
The knight carries the brachet.
The lady says that she wants the brachet.
The brachet bays at Sir Tor.
[PK: Only hunting dogs bay]
--> (defineNoun "brachet")
Definition of brachet:
Class Inclusions: hound, dog,
Possible Actions: bite buttock, bay, hunt,
Possible Properties: valuable, small, white,
I.e. A brachet is a hound (a kind of dog) that can bite, bay, and hunt,
and that may be valuable, small, and white.
CVA as Symbol Manipulation
• We “solved” each sentence for the unknown word
– in terms of the rest of the text
together with our background knowledge
• Just as we can solve an algebra problem
– in terms of the rest of the equation
• By manipulating symbols
– which is what computers do!
Computational
Natural-Language Understanding
• What else is needed?
– besides symbol manipulation
Mind as a Symbol-Manipulation System
To understand language, a cognitive agent must:
• Take discourse as input
• Understand ungrammatical input
• Make inferences & revise beliefs
• Make plans
– For speech acts
– To ask/answer questions
– To initiate conversation
• Understand plans
– Speech-act plans of interlocutor
•
•
•
•
Construct user model
Learn (about world, language)
Have background/world/commonsense knowledge
Remember
– What it heard, learned, inferred, revised
= have a mind!
• All of this can be done by computers manipulating symbols!
The End
?
A Natural-Language-Understanding
Puzzle
• Mice eat cheese.
• Which mice?
– Mice that cats chase eat cheese.
– Mice cats chase eat cheese
An NLU Puzzle (cont’d)
• Dogs dogs dog dog dogs.
– To “dog” = to follow someone or something closely
– Dogs (that other dogs follow) follow (other) dogs
An NLU Puzzle (cont’d)
• Buffalo buffalo buffalo buffalo buffalo
– to “buffalo” = to intimidate someone or something
– Buffalo (that other buffalo intimidate) intimidate (other)
buffalo.
An NLU Puzzle (cont’d)
• What about the buffalo in the Buffalo zoo?
– They are the Buffalo buffalo.
– They are very intimidating!
– Buffalo buffalo Buffalo buffalo buffalo buffalo
Buffalo buffalo
• Buffalo in the Buffalo zoo (the Buffalo buffalo),
who are intimidated by other Buffalo buffalo,
also intimidate other Buffalo buffalo.
An NLU Puzzle (cont’d)
• The Buffalo buffalo intimidate in a very
special way, called “Buffalo buffaloing”
• Buffalo buffalo Buffalo buffalo Buffalo
buffalo Buffalo buffalo Buffalo buffalo
– The Buffalo buffalo, who are buffaloed in the
Buffalo way by other Buffalo buffalo, buffalo
other Buffalo buffalo in the Buffalo way :-)