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Doing Philosophy

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Title: Doing Philosophy


1
Doing Philosophy
  • Philosophical theories are not primarily
  • about facts. Therefore, there is no right or
    wrong.
  • Philosophical arguments are well-argued opinions.
  • A philosophy course such as this concerns both
    facts and opinions, e.g.
  • What is functionalism (fact)? What is the
    problem of multiple realization (fact)? Is
    functionalism a good theory of the mind
    (opinion)? Is materialism a better theory than
    dualism (opinion)?

2
Doing Philosophy in this Course
  • Ask questions
  • in class
  • on the course blog
  • Think for yourself.
  • Justify your opinions with good logical
    arguments, also can appeal to scientific evidence
    and personal experience

3
Tutorials
  • There are four tutorial groups
  • All groups meet in the Philosophy Department,
    Room MB 305
  • Group 1 Thurs. 200
  • Sept. 20, Oct. 4, Nov. 1, Nov. 15
  • Group 2 Tues. 200
  • Sept. 25, Oct. 23, Nov. 6, Nov. 20
  • Group 3 Tues. 300
  • Sept. 25, Oct. 23, Nov. 6, Nov. 20
  • Group 4 Tues. 100
  • Oct. 2, Oct. 30, Nov. 13, Nov. 27
  • Please sign up today in the break. Otherwise,
    send me an email.

4
Functionalism
  • Things are defined by their functions
  • Two ways to define function
  • Function inputs and outputs (machine
    functionalism)
  • e.g. mathematical function, e.g. , -, x, /
  • 2 x 3 6, when input is 2 and 3, output is 6
  • Multiple realizability can be realized in
    different materials or through different
    processes

5
  • Functionalism defined as inputs and outputs
    continued
  • e.g. beliefs, desires
  • I am thirsty (i.e. I desire water) is defined
    in terms of inputs and outputs. When there are
    inputs x and y, there is output z
  • Input Output
  • (x) Water is available (z) I drink water
  • (y) There is no reason not to drink the water

6
  • 2) Function use (teleological functionalism)
  • Function is defined by what something does.
  • e.g. a heart pumps blood.
  • e.g. a belief plays a role in reasoning a
    premise in a practical syllogism
  • Premise 1 I believe x is water
  • Premise 2 I desire water
  • Premise 3 There is no reason not to drink x
  • Conclusion I drink x

7
  • No matter if you interpret functional as an
    input-output relation (machine functionalism) or
    use (teleological functionalism), mental states,
    such as thirst are multiply realizable.
  • A computer can conduct multiplication.
  • An alien can have thirst, pain, etc.
  • A computer can have thirst, pain, etc.

8
Functional definition of mind
  • If x acts like a mind, it is a mind.
  • If, when compared to a mind given similar inputs,
    x gives similar outputs, x is a mind.
  • If a computer can converse (take part in
    linguistic input and output exchanges/play the
    role of an intelligent conversational partner)
    just like a person, the computer is as
    intelligent as a person. It has a mind.

9
The Chinese Room Argument
10
Background
  • Thought Experiments
  • Instead of scientific experiments, philosophers
    have thought experiments
  • Thought experiments are conducted in the
    imagination
  • They test concepts looking for consistency and
    contradictions, often using intuitions to make
    judgments

11
  • The Turing Test
  • In 1950, a computer scientist, Alan Turing,
  • wanted to provide a practical test to answer
  • Can a machine think?
  • His solution -- the Turing Test
  • If a machine can conduct a conversation so well
    that people cannot tell whether they are talking
    with a person or with a computer, then the
    computer can think. It passes the Turing Test.
  • In other words, he proposed a functional
    solution to the question, can a computer think?

12
  • There are many modern attempts to produce
    computer programs that pass the Turing Test.
  • In fact, in 1991 Dr. Hugh Loebner started the
    annual Loebner Prize competition, with prize
    money offered to the author of the computer
    program that performs the best on a Turing Test.
  • The winner of the Loebner prize in 2004 was a
    program called ALICE.
  • You can try her (and other talkbots) out on this
    website
  • http//cogsci.ucsd.edu/asaygin/tt/ttest.htmltalk
    tothem

13
Searles Chinese Room Argument
  • John Searle
  • Famous philosopher at the
  • University of California, Berkeley
  • Most well-known in philosophy of language,
    philosophy of mind and consciousness studies
  • Wrote Minds, Brains and Programs in 1980, which
    described the Chinese Room Argument

14
Searles Chinese Room Argument
  • The Chinese Room argument is one kind of
    objection to functionalism, specifically to the
    Turing Test
  • Also an attack on strong AI
  • Searle makes distinction between strong AI and
    weak AI
  • Strong AI the appropriately programmed computer
    really is a mind, in the sense that computers,
    given the right programs can be literally said to
    understand
  • Weak AI Computers can simulate thinking and help
    us to learn about how humans think
  • Searle objects only to strong AI.

15
The Chinese Room
  • Searle cannot understand any Chinese.
  • He is in a room with input and output windows,
    and a list of rules about manipulating Chinese
    characters.
  • The characters are all squiggles and squoggles
    to him.
  • Chinese scripts and questions come in from the
    input window.
  • Following the rules, he manipulates the
    characters and produces a reply, which he pushes
    through the output window.

16
  • The Chinese answers that Searle produces are very
    good.
  • In fact, so good, no one can tell that he is not
    a native Chinese speaker!
  • Searles Chinese Room passes the Turing Test. In
    other words, it functions like an intelligent
    person.
  • Searle has only conducted symbol manipulation,
    with no understanding, yet he passes the Turing
    Test.
  • Therefore, passing the Turing Test does not
    ensure understanding.
  • In other words, although Searles Chinese Room
    functions like a mind, it is not a mind, and
    therefore functionalism is wrong.

17
  • Syntax vs. semantics
  • Searle argued that computers can never understand
    because computer programs are purely syntactical
    with no semantics.
  • Syntax the rules for symbol manipulation, e.g.
    grammer
  • Semantics understanding what the symbols (e.g.
    words) mean
  • Syntax without semantics The bliggedly blogs
    browl aborigously.
  • Semantics without syntax Milk want now me.

18
  • Searle concludes that symbol manipulation alone
    can never produce understanding.
  • Computer programming is only symbol manipulation.
  • Computer programming can never produce
    understanding.
  • Strong AI is false and functionalism is wrong.

19
  • What could produce real understanding?
  • Searle it is a biological phenomenon and only
    something with the same causal powers as brains
    can have understanding.

20
Objections
  • The Systems Reply
  • Searle is part of a larger system. Searle doesnt
    understand Chinese, but the whole system (Searle
    room rules) does understand Chinese.
  • The knowledge of Chinese is in the rules
    contained in the room.
  • The ability to implement that knowledge is in
    Searle.
  • The whole system understands Chinese.

21
  • Searles Response to the Systems Reply
  • Its absurd to say that the room and the rules
    can provide understanding
  • 2) What if I memorized all the rules and
    internalized the whole system. Then there would
    just be me and I still wouldnt understand
    Chinese.
  • Counter-response to Searles response
  • If Searle could internalize the rules, part of
    his brain would
  • understand Chinese. Searles brain would house
    two
  • personalities English-speaking Searle and
    Chinese-
  • speaking system.

22
The Robot Reply What if the whole system was put
inside a robot? Then the system would interact
with the world. That would create understanding.
23
Searle inside the robot
24
  • Searles response to the Robot Reply
  • The robot reply admits that there is more to
    understanding than mere symbol manipulation.
  • 2) The robot reply still doesnt work. Imagine
    that I am in the head of the robot. I have no
    contact with the perceptions or actions of the
    robot. I still only manipulate symbols. I still
    have no understanding.
  • Counter-response to Searles response
  • Combine the robot reply with the systems reply.
    The robot as a whole understands Chinese, even
    though Searle doesnt.

25
  • The Complexity Reply
  • Really a type of systems reply.
  • Searles thought experiment is deceptive. A room,
    a man with no understanding of Chinese and a few
    slips of paper can pass for a native Chinese
    speaker.
  • It would be incredibly difficult to simulate a
    Chinese speakers conversation. You need to
    program in knowledge of the world, an individual
    personality with simulated life history to draw
    on, and the ability to be creative and flexible
    in conversation. Basically you need to be able to
    simulate the complexity of an adult human brain,
    which is composed of billions of neurons and
    trillions of connections between neurons.

26
  • Complexity changes everything.
  • Our intuitions about what a complex
  • system can do are highly unreliable.
  • Tiny ants with tiny brains can
  • produce complex ant colonies.
  • Computers that at the most basic level are just
    binary switches that flip from 1 to 0 can play
    chess and beat the worlds best human player.
  • If you didnt know it could be done, you would
    not believe it.
  • Maybe symbol manipulation of sufficient
    complexity can create semantics, i.e. can produce
    understanding.

27
Conclusion
  • The Turing Test
  • Searle is probably right about the Turing Test.
  • Simulating a human-like conversation probably
    does not guarantee real human-like understanding.
  • Certainly, it appears that simulating
    conversation to some degree does not require a
    similar degree of understanding. Programs like
    ALICE presumably have no understanding at all.
  • .

28
  • 2) Functionalism
  • Functionalists can respond that the functionalist
    identification of the of the room/computer and a
    mind is carried out at the wrong level.
  • The computer as a whole is a thinking machine,
    like a brain is a thinking machine. But the
    computers mental states may not be equivalent to
    the brains mental states.
  • If the computer is organized as a really long
    list of questions with canned answers, the
    computer does not have mental states such as
    belief or desire.
  • But if the computer is organized like a human
    mind, with concepts, complex organization and
    homuncular modules, the computer can have
    beliefs, desires, etc.

29
3) Strong AI Could an appropriately programmed
computer have real understanding? Too early to
say. I am not convinced by Searles argument that
it is impossible. The right kind of programming
with the right sort of complexity may yield true
understanding. e.g. homuncular
modularity mixing of levels self-updating
30
  • 4) Syntax vs. Semantics
  • How can semantics (meaning) come out of symbol
    manipulation? How can 1s and 0s result in real
    meaning? Its mysterious. But then how can the
    firing of neurons result in real meaning? Also
    mysterious.
  • One possible reply meaning is use
    (Wittgenstein). Semantics is syntax at use in the
    world.

31
  • 5) Qualia
  • Qualia raw feels phenomenal experience
    what it is to be like something
  • Can a computer have qualia? Again, it is hard to
    understand how silicon and metal can have
    feelings. But it is no easier to understand how
    meat can have feelings.
  • If a computer could talk intelligently and
    convincingly about its feelings, we would
    probably ascribe feelings to it. But would we be
    right?

32
  • 5) Searles claim understanding can only occur
    in biological systems with the same causal
    properties as the brain
  • There is no basis for this hypothesis. It is
    unclear what special causal properties the brain
    meant to have. I doubt that Searle is right about
    this.

33
Readings for next week
  • Sterelny, Kim, The Representational Theory of
    Mind, Section 1.3, pgs. 11-17
  • (on reserve in Philosophy Dept.)
  • Sterelny, Kim, The Representational Theory of
    Mind, Section 3.1-3.4, pgs. 42-49 (on reserve in
    Philosophy Dept.)

34
More optional readings
  • On the Chinese Room
  • Searle, John. R. (1990), Is the Brain's Mind a
    Computer Program? in Scientific American, 262,
    pgs. 20-25 (in main library)
  • Churchland, Paul, and Patricia Smith Churchland
    (1990) Could a machine think? in Scientific
    American 262, pgs. 26-31 (in main library)
  • On modularity of mind
  • Fodor, Jerry A. (1983), The Modularity of Mind,
    pgs. 1-21 at
  • http//ruccs.rutgers.edu/forums/seminar3_spring05
    /Fodor_1983.pdf
  • Pinker, Steven (1999), How the Mind Works,
    William James Book Prize Lecture at
  • www3.hku.hk/philodep/joelau/wiki/pmwiki.php?nMai
    n.Pinker-HowTheMindWorks
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