The Birth of the Computer

1
The Birth of the Computer
2
Foundations

• The theory of computation and the practical
  application it made possible  the computer  was
  developed by an Englishman called Alan Turing.

3
Alan Turing

• 1912 (23 June) Birth, Paddington, London
• 1931-34 Undergraduate at King's College,
  Cambridge University
  
• 1932-35 Quantum mechanics, probability, logic
• 1936 The Turing machine, computability,
  universal machine
  
• 1936-38 Princeton University. Ph.D. Logic,
  algebra, number theory
  
• 1938-39 Return to Cambridge. Introduced to
  German Enigma cipher machine
  
• 1939-40 The Bombe, machine for Enigma decryption

• 1939-42 Breaking of U-boat Enigma, saving battle
  of the Atlantic
  
• 1946 Computer and software design leading the
  world.
  
• 1948 Manchester University
• 1949 First serious mathematical use of a
  computer
  
• 1950 The Turing Test for machine intelligence
• 1952 Arrested as a homosexual, loss of security
  clearance
  
• 1954 (7 June) Death (suicide) by cyanide
  poisoning, Wilmslow, Cheshire.
  
• from Andrew Hodges http//www.turing.org.uk
  /turing/

4
The Decision Problem

• In 1928 the German mathematician, David Hilbert
  (1862-1943), asked whether there could be a
  mechanical way (i.e. by means of a fully
  specifiable set of instructions) of determining
  whether some statement in a formal system like
  arithmetic was provable or not.
• In 1936 Turing published a paper the aim of which
  was to show that there was no such method.
  
• On computable numbers, with an application to
  the Entscheidungs problem. Proceedings of the
  London Mathematical Society, 2(42)230-265).

5
The Turing Machine

• In order to argue for this claim, he needed a
  clear concept of mechanical procedure.
  
• His idea which came to be called the Turing
  machine  was this
  
• (1) A tape of infinite length
• (2) Finitely many squares of the tape have a
  single symbol from a finite language.
  
• (3) Someone (or something) that can read the
  squares and write in them.

• (4) At any time, the machine is in one of a
  finite number of internal states.
  
• (5) The machine has instructions that determine
  what it does given its internal state and the
  symbol it encounters on the tape. It can
  
• ? change its internal state
• ? change the symbol on the square
• ? move forward
• ? move backward
• ? halt (i.e. stop).

6
Current state 1 If current state 1 and curre
nt symbol 0 then new state 10 new symbol 1

move right
0
1
0
1
1
1
7
Current state 10 If current state 1 and curr
ent symbol 0 then new state 10 new symbol
1
move right
1
1
1
1
1
8
1
1
1
1
1
9
Functions

• It is essential to the idea of a Turing machine
  that it is not a physical machine, but an
  abstract one a set of procedures.
  
• It makes no difference whether the machine is
  embodied by a person in a boxcar on a track, or a
  person with a paper and pencil, or
  
• a smart and well-
• trained flamingo.

10
Turings Theorem

• In the 1936 paper Turing proved that there are
  general-purpose Turing machines that can
  compute whatever any other Turing machine.
  
• This is done by coding the function of the
  special-purpose machine as instructions of the
  other machine  that is by programming it. This
  is called Turings theorem.
• These are universal Turing machines, and the idea
  of a coding for a particular function fed into a
  universal Turing machine is basically our
  conception of a computer and a stored program.
• The concept of the universal Turing machine is
  just the concept of the computer as we know it.

11
Computers and the Mind
12
Can Machines Think?

• In Computing machinery and intelligence,
  written in 1950, Turing asks whether machines can
  think.
  
• He claims that this question is too vague, and
  proposes, instead, to replace it with a different
  one.
  
• That question is Can machines pass the
  imitation game (now called the Turing test)? If
  they can, they are intelligent.
  
• Turing is thus the first to have offered a
  rigorous test for the determination of
  intelligence quite generally.

13
The Turing Test

• The game runs as follows. You sit at a computer
  terminal and have an electronic conversation. You
  dont know who is on the other end it could be a
  person or a computer responding as it has been
  programmed to do.
• If you cant distinguish between a human being
  and a computer from your interactions, then the
  computer is intelligent.
  
• Note that this is meant to be a sufficient
  condition of intelligence only. There may be
  other ways to be intelligent.

14
Functionalism

• In 1960 Hilary Putnam (b. 1926) used the idea of
  a Turing machine to develop a view about the
  mind.
  
• This view is called functionalism.

15
Functionalist Analysis

• Functionalism holds that a mental state can be
  exhaustively characterized by describing
  
• (a) the input that typically brings it about
• (b) its relations to other mental states and
• (c) the output it tends to produce.
• So, for example, we can characterize pain as the
  mental state
  
• (a) typically brought about by damage to the
  body
  
• (b) that is closely related to anger, regret, and
  so on and
  
• (c) that tends to produce shouting, crying, and
  the like.

16
Computationalism

• An extension of this idea, due primarily to Jerry
  Fodor (b. 1935) and one that Fodor traces back
  to Turing as well is the view that thought is
  essentially a series of moves in a Turing
  machine.
• It is, in effect, the manipulation of symbols on
  an abstract tape the performing of
  computations.
  
• This view is called computationalism, and it is
  the only real theory weve got about what thought
  is.

Central to this view is the idea that the form of
thought (its syntax) e.g., the 0s and 1s on
the tape  determines its content or meaning (its
semantics).
17
Artificial Intelligence
18
The Church-Turning Thesis

• Turing, and a logician called Alonzo Church
  (1903-1995), independently developed the idea
  (not yet proven by widely accepted) that whatever
  can be computed by a mechanical procedure can be
  computed by a Turing machine.
• This is known as the Church-Turing thesis.

19
AI The Argument

• Weve now got the materials to show that AI is
  possible
  
• P1 Any function that can be computed by a
  mechanical procedure can be computed by a Turing
  machine. (Church-Turing thesis)
  
• P2 Thinking is nothing more than the computing
  of functions by mechanical procedures (i.e.,
  thinking is symbol manipulation).
  (Functionalist-Computationalist thesis)
• C1 Therefore, thinking can be performed by a
  Turing machine.
  
• P3 Turing machines are multiply realizable. In
  particular, they can be realized by computers,
  robots, etc.
  
• ? It is possible to build a computer, robot,
  etc. that can think. That is, AI is possible.

20
Searles Challenge The Chinese Room Argument
21
John Searle (b. 1932)
22
A Distinction

• Strong AI The research program whose aim is to
  produce entities with real intelligence.
  
• Weak AI The research program whose aim is to
  produce entities that simulate real
  intelligence.
  
• Compare the weather a computer that models
  weather patterns is simulating the weather rather
  than recreating it.
  
• Searles argument is directed at strong AI.

23
Intentionality

• Searle claims that it is not possible (with
  standard computers) to build a machine that has
  intentionality.
  
• Intentionality is the property of a mental state
  that makes it about something in the world.
  
• Exactly what intentionality amounts to, however,
  is not crucial to the argument.
  
• For our purposes, Searles aim is to argue that a
  computer cant have some of the features we
  associate with thought.
  
• In particular, it doesnt have states that are
  meaningful that have semantic properties. In
  the case well look at, the computer doesnt have
  understanding.

24
Searles Challenge

• Searles argument takes as an example a
  story-understanding program from 1977 due to
  Schank and Abelson.
  
• But his argument applies to any form of strong AI.

25
The Chinese Room

• The Chinese Room is a thought experiment.
• Thought experiments are used not only in
  philosophy what matters is not whether the
  experiment is possible but whether it is
  coherent. If it is coherent, what does it show?

26
Elements

• The room contains an English speaker who does not
  understand Chinese.
  
• There is a slot in the door through which symbols
  in Chinese pass into and out of the room.
  
• The person in the room has a rule-book that tells
  him what symbols to produce in response to
  symbols introduced into the room when you get a
  squiggle-squiggle, produce a squoggle-squoggle.

27
The Turing Test Again

• The person in the room gets good enough to
  convince a native Chinese speaker that he
  understands Chinese.
  
• In other words, the Chinese Room passes the
  Turing test (conducted in Chinese).
  
• But, of course, the man in the room doesnt
  understand Chinese!

28
First Argument

• With these ideas in hand, we can construct an
  argument concerning the Turing test
  
• (P1) Passing the Turing test is supposed to be a
  sufficient demonstration of intelligence.
  
• (P2) The person in the Chinese Room passes the
  Turing test.
  
• (P3) However, the person in the room does not
  have the relevant intelligence (the ability to
  understand Chinese).
  
• ? (C) The Turing test is not an adequate test of
  intelligence.
  

29
Syntax and Semantics

• The more general and powerful argument made
  possible by the Chinese Room case concerns the
  very possibility of strong AI given current
  computers.
• That argument depends on the distinction between
  syntax and semantics which weve already
  encountered.
  
• Recall that the syntax of a string of symbols
  concerns the rules for ordering symbols in the
  right way.
  
• But these rules dont tell you enough to know
  what the symbols mean. That is, they dont give
  you semantics.

30
Illustration

• Consider the sentence
• All members of the NDP drink Boréale.
• It is easy to tell that this is a good sentence.
  The right sort of words (e.g. nouns, verbs, etc.)
  are used unlike
  
• All members of the NDP Boréale.
• and they are used in the right order unlike
• Members Boréale all of drink NDP the.
• But you dont know what this sentence means.
• This shows that syntactical properties dont give
  you semantic properties informally grammar
  doesnt reveal meaning.

31
Second Argument

• We can now formulate Searles main argument
• (P1) Computer programs are purely syntactical
  things they operate on meaningless symbols.
  
• (P2) Minds have semantic properties they have
  states that have meanings.
  
• (P3) The Chinese room shows that syntax is not
  the same thing as, nor is it sufficient for,
  semantics.
  
• ? (C1) Therefore, computer programs are not the
  same thing as, nor sufficient for, minds.
  
• ? (C2) Therefore, AI is impossible (with
  computers as we know them).

32
Some Remarks

• It is important to see that the argument does not
  (and was not intended) to show that machines
  cant think, or that artificial intelligence of
  any kind is impossible.
• Searle accepts both of these claims.
• Rather, it is designed to show that a computer
  cannot have genuine psychological properties
  simply in virtue of its input and output
  relations  that is, simply in virtue of its
  program.
• On Searles view, thinking requires being a
  physical thing with special causal properties.
  
• A machine that was as intelligent as the brain
  would have to duplicate the causal properties of
  the brain.

33
Learning Machines

• There are computers that operate on rather
  different principles from Turing machines.
  
• These machines, usually called connectionist or
  neural networks, change their structure in
  response to input and output. They learn.
  
• Whether these kinds of machines could be truly
  intelligent or not depends on how you interpret
  what they are doing.
  
• Some people think they are just special kinds of
  Turing machines, in which case, Searles argument
  applies to them too.
  
• Other people think they dont have programs so
  they fall outside the scope of Searles argument.

34
Functionalism and Computationalism

• Finally, if Searle is right, then both
  functionalism and computationalism, as theories
  of the mind, are false.
  
• The man in the Chinese room exhibits the right
  functions and manipulates the right symbols to
  behave as if he understood Chinese. But he
  doesnt.
• Merely exhibiting particular functional relations
  (including manipulating symbols according to
  particular rules) is not enough for thought.
  
• Computation alone is not sufficient for thought.

35
Replies

• Searle considers a number of possible objections
  to his argument in the original paper.
  
• In the last twenty-two years a huge literature
  has grown up around the argument.
  
• (Searle says in an article from 2002 I have
  already responded to more criticisms of the
  Chinese Room Argument than to all of the
  criticisms of all of the other controversial
  philosophical theses that I have advanced in my
  life.)
• Well consider a few important lines of argument
  here.

36
The Systems Reply

• According to this line of thought, Searle commits
  the fallacy of taking the part for the whole.
  
• The argument says that the man in the room
  doesnt understand Chinese, and he concludes from
  this that the Chinese room as a whole doesnt.
  
• But, so the objection runs, the man, the
  rule-book, the symbols, and all the other
  relevant elements of the function of the Chinese
  room do understand Chinese.

37
Searles Rejoinder

• Searle has two main replies.
• First he says that the man in the room could
  internalize all of the relevant parts of the
  procedure he could memorize the rule-book he
  could work outdoors and so on.
• Whatever was in the Chinese room initially is now
  entirely in the mans mind. But he still doesnt
  understand Chinese.
  
• Second, he claims that it is utterly implausible
  to say that while the man doesnt understand
  Chinese, the man plus some bits of paper and a
  rule-book do.

38
The Robot Reply

• There is no understanding in the Chinese room
  because the relations between the symbols
  manipulated by the man in the room and the things
  they refer to are missing.
• If we created a robot that had the same symbols
  and rule-book but and could interact with the
  environment, the robot would understand Chinese.

39
Searles Rejoinder

• Searle notes, first, that this reply already
  concedes that the basic premise of AI is false
  syntax is not enough for semantics. You need
  causal interaction too.
• Second, Searle asks us to imagine a sort of
  mobile Chinese room a robot it gets input from
  the environment and produces behavior.
  
• So what? The man inside the room is still only
  engaging in transactions with symbols (even if
  they are symbols representing the outside world).
  
• The robot can pass a more complicated Turing
  test, but the Turing test is always inadequate to
  measure intelligence The problem remains.

40
The Brain Simulator Reply

• Suppose that instead of manipulating symbols in
  Chinese the man in the room simulates the neuron
  firings of a brain that is in the process of
  understanding some sentence in Chinese (or
  producing a sentence in Chinese).
• Surely then the Chinese room would understand
  Chinese because it is doing just what the brain
  of a Chinese speaker does.

41
Searles Rejoinder

• Adapt the Chinese room so that it contains an
  elaborate set of water pipes with valves.
  
• In response to input in Chinese, the man in the
  room opens and shuts some of the valves in a
  particular way where each valve opening or
  closing simulates what some neuron does. As a
  result, out pops the correct response in
  Chinese.
• The man still doesnt understand Chinese nor do
  the pipes!
  
• Why? Because the Chinese room merely simulates
  the brain. It captures the structure of the
  brains activity just as a program captures the
  structure of what a mind does. But in both cases,
  the causal relations arent there, so there is no
  mind.

42
The Combination Reply

• Take all of the suggestions weve just looked at
   a computer in a robot running a program that
  simulates what the brain does  and you would
  have genuine understanding.

43
Searles Rejoinder

• None of the features of this solution worked
  separately, and there is no reason to think that
  putting them together produces something new.

44
The Other Minds Reply

• How do we know in ordinary life whether someone
  understands Chinese? If they behave as if they
  do if they can speak Chinese.
  
• Since the Chinese room behaves as if it speaks
  Chinese, then one ought to say that it
  understands Chinese for the same reason as one
  says that a Chinese-speaker understands Chinese.

45
Searles Rejoinder

• Notice first that this is just a defense of the
  Turing test. Since Searles argument purports to
  demonstrate that the Turing test is inadequate,
  this begs the question against Searle.
• In addition, Searle says that it misses the
  point. The important issue is not how we decide
  whether someone understands Chinese but what is
  involved in understanding Chinese.
• The argument shows that computation is not enough
  for understanding. If one were to attribute
  understanding to the Chinese room, one would get
  the wrong answer even though the criterion used
  gives the right answer in the case of Chinese
  speakers.

46
The Many Mansions Reply

• Even if Searle is right that programming alone is
  insufficient for AI, there might be other ways of
  producing intelligent machines.

47
Searles Rejoinder

• This also misses the point because it defines AI
  in a trivial way as whatever produces artificial
  intelligence.
  
• The actual hypothesis of the strong AI research
  program is that intelligence can be produced by
  programming alone. The Chinese room argument
  shows that this is false.
• If the hypothesis is trivialized, then the
  Chinese room argument doesnt apply, but only
  because, in effect, AI has become a self-sealing
  doctrine.

48
Concluding Note

• There is wide consensus in cognitive science and
  philosophy that the Chinese room argument is
  wrong or worse badly flawed and not deserving
  of its fame.
• But the argument continues to attract serious
  criticism.
  
• And it continues to elicit disagreement among its
  critics about exactly where it goes wrong!
  
• Dead views typically do neither.

49
Later Searle Syntax and Biology
50
Syntax Again

• The Chinese Room argument is supposed to show
  that syntax is not sufficient for semantics and
  therefore not sufficient for minds.
  
• Searle assumes that the syntactical properties of
  a computer are uncontroversial.
  
• In some later work, however, he argues that even
  the notion of the syntax of computer
  representations is problematic.
  
• He infers from this something stronger even than
  the conclusion of the Chinese Room argument
  artificial intelligence is not only not possible
  (with current computers) it is incoherent!

51
Observer-Dependence

• The basic idea on which Searles argument depends
  is the distinction between something being
  observer-independent and observer-dependent.
  
• Something is observer-independent if that thing
  would exist even if there was no one to observer
  them.
  
• Something is observer-dependent if its existence
  requires the existence of human observers.
  
• Some observer-independent things are mass,
  molecules, cells.
  
• Some observer-dependent things are political
  parties, money, hockey.

52
Syntax and Observers

• Is syntax an observer-independent or
  observer-independent property?
  
• Consider again the sentence
• All members of the NDP drink Boréale.
• exhibits correct syntax only relative to the
  rules of English.
  
• But of course if there were no human beings,
  English wouldnt exist, nor would English
  syntax.
  
• Clearly, then, syntax is an observer-relative
  feature of symbols.
  
• As Searle says Syntax is not intrinsic to
  physics.

53
Computation Again

• The idea, roughly, is that the words in English
  only have syntactic properties because people
  treat them as symbols rather than as mere marks
  on paper or sounds.
• What follows from this?
• Computers manipulate symbols according to
  syntactic rules.
  
• Therefore, the notion of computation is a
  syntactic one.
  
• But if syntax is observer-relative, and
  computation is defined syntactically, then
  computations are also observer-dependent
  entities.

54
Semantics Again

• What about semantics? Is it observer-dependent or
  observer-independent?
  
• The fact that I understand the sentence
• All members of the NDP drink Boréale.
• does not depend on there being an observer. I
  would understand that sentence even if there was
  no one in the world but me and I was not
  observing myself understanding the sentence.
• So the semantic properties of the mind seem to be
  observer-independent.

55
The Argument

• With these further ideas about syntax and
  semantics, Searle can make a final assault on
  AI
  
• (P1) Computation is observer-dependent.
• (P2) Minds have semantic properties.
• (P3) Semantic properties of minds are
  observer- independent.
  
• ? (C) Therefore, computer programs are not
  necessary for indeed, not even relevant to
  minds.
  
• (Recall that the conclusion of the Chinese Room
  argument was that computer programs are not
  sufficient for minds.)

56
Language Again

• Recall that at the beginning of the course we
  distinguished different things that one can do
  with language linguistic acts, speech acts, and
  conversational acts.
• Linguistic acts involve saying something
  meaningful.
  
• If Searle is right, then computers cant perform
  linguistic acts because they cant attribute
  meanings to language.
  
• Indeed, even the basic feature of linguistic acts
   putting words together in the right order is
  dependent on the intentions of a programmer.
  
• So if Searle is right, then computers cant do
  even the most basic things with language and
  cannot therefore be anything like human minds.

57
The Bottom Line

• Computer programs are not even in the running to
  be the basis for minds.
  
• They are just the wrong kind of thing.

58
Searles Alternative

• Well, if programs are not relevant, what is?
• Or, as it is sometimes put, what could cognition
  be if not computation?
  
• In brief, Searle thinks that mentality is a
  biological phenomenon.
  
• He calls this view biological naturalism.

59
The Basic Idea

• Think of water molecules. Each molecule has a
  number of physical properties  molecular weight,
  charge, and so on.
  
• But when youve got a lot of molecules together,
  new properties emerge liquidity, transparency,
  and so on.
  
• The brain is made up of lots of neurons each of
  which has a number of physical properties.
  
• When taken together, however, new properties
  emerge understanding, consciousness  semantic
  properties.
  
• Mental properties are properties of complex
  biological systems.

60
The Future of AI

• Where does that leave AI?
• According to Searle, we know that AI is possible
  brains are machines and they are intelligent.
  
• So if we want to create AI, we have to learn (1)
  how brains work and (2) how to create artificial
  brains.
  
• There may be other kinds of systems that can
  think too, but we have no idea what they might be
  like.
  
• Our best bet, therefore is the brain. Thus, the
  future of AI lies in neurobiology.