Functionalism

1
Functionalism

• Some context from Stanford Encyclopedia of
  Philosophy
• Behaviorism ... attempts to explain behavior
  without any reference whatsoever to mental states
  and processes
• http//plato.stanford.edu/entries/functiona
  lism/2.3
• Functionalism in the philosophy of mind is the
  doctrine that what makes something a mental state
  of a particular type does not depend on its
  internal constitution, but rather on the way it
  functions, or the role it plays, in the system of
  which it is a part.
• http//plato.stanford.edu/entries/functiona
  lism/

2
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

3

• 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

4

• 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

5

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

6
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.

7
The Chinese Room Argument
8
Background

• Thought Experiments
• Instead of empirical experiments, philosophers
  and logicians can conduct thought experiments
• Thought experiments may be carried out using
  natural languages, graphic visualizations, and/or
  formalized versions of their relevant aspects
• They test concepts and theories for consistency,
  completeness, etc., using critical intuition
  aided by logic tools (e.g., reasoners) for
  evaluation

9

• 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?

10

• There are many modern attempts to produce
  computer programs (chatterbots) that pass the
  Turing Test.
• 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. You can
  track (and perhaps try) the annual
  winnershttp//en.wikipedia.org/wiki/Loebner_priz
  eWinners
• But Turing Tests have been objected to on several
  groundshttp//en.wikipedia.org/wiki/Turing_test
  Weaknesses_of_the_test

11
Searles Chinese Room Argument

• John Searle
• Famous philosopher at 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
• ... whatever purely formal principles you put
  into the computer, they will not be sufficient
  for understanding, since a human will be able to
  follow the formal principles without
  understanding anything.

12
Searles Chinese Room Argument

• The Chinese Room argument is one kind of
  objection to functionalism, specifically to the
  Turing Test
• Searle makes distinction between strong AI and
  weak AI, objecting (only) to strong 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
• NB Searle knows that he understands English
  and?by contrast?that he does not understand any
  Chinese

13
Summary of SearlesChinese Room Thought
Experiment

• Searle is in a room with input and output
  windows, and a list of rules, in English, about
  manipulating Chinese characters.
• The characters are all meaningless squiggles and
  squoggles to him.
• Chinese texts and questions come in from the
  input window.
• Following the rules, he manipulates the
  characters and produces each reply, which he
  pushes through the output window.

14

• The answers in Chinese 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 in Chinese.
• Therefore, passing the Turing Test does not
  ensure understanding.
• In other words, although Searles Chinese Room
  functions like a mind, he knows (and we in an
  analogous foreign-language room experiment would
  know) it is not a mind, and therefore
  functionalism is wrong.

15
Grailog Classes, Instances, Relations
Classes with relations
subClassOf
understand
instanceOf
Language
understand
negation
Chinese
English
lang
lang
lang
lang
lang
haveLanguage
with
to
for
texts
questions
rules
replies
with
for
apply
use
Searle
Wang
Searle-replyi
Wang-replyi
distinguishable
Instances with relations
16

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

17

• 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.

18

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

19
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.

20

• 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.

21
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.
22
Searle inside the robot
23

• 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 does not.

24

• 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.

25

• 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.

26

• Possible Response to the Complexity Reply
• See Response to the Systems Reply
• 2) Where would be the quantitative-qualitative
  transition?
• Counter-response to that response
• What would happen if Searles Chinese-speaking
  subsystem would become as complex as
  theEnglish-speaking rest of his linguistic mind?

27
Searles criticism of strong AIs mind-program
analogy
Searles criticism of strong AIs analogymind
is to brain as program is to computerseems
justified since mental states and events are
literally a product of the operation of the
brain, but the program is not in that way a
product of the computer.
28
Classes and relations
tangible
intangible
produce
animate
run
inanimate
Classes brain, mind, computer, program Binary
relations produce, run
29
Instances
tangible
intangible
produce
animate
produce
run
inanimate
run
Classified instances brains b1, b2 minds m1,
m2 computers
c1, c2 program p
30
A theory claiming two assertions over the classes
and relations
In EnglishDifferent brains (will) produce
different minds. Different computers (can) run
the same program. In Controlled
English, equivalent to first-order logic with
(negated) equality For all brains B1, B2 and
minds M1, M2 it holds that if B1 ? B2 and B1
produces M1 and B2 produces M2 then M1 ?
M2. There exist computers C1, C2 and program P
such that C1 ? C2 and C1 runs P and C2 runs P.
31
A theory claiming two assertions over the classes
and relations
If produce and run would be the same
relation, produce run, and brain and computer
would be the same class, brain computer,
and mind and program would be the same
class, mind program, then this would lead to an
inconsistency between the two assertions. Hence,
according to the theory, the relations or one
of the pairs of classes must be different.
32
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
  the 2008 chatterbots presumably have no
  understanding at all.

33

• 2) Functionalism
• Functionalists can respond that the functionalist
  identification 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 nothing but one
  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, e.g. with learnable, interlinked,
  modularized concepts, facts, and rules, the
  computer could have beliefs, desires, etc.

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3) Strong AI Could an appropriately programmed
computer have real understanding? Too early to
say. We might not be convinced by Searles
argument that it is impossible. The right kind
of programming with the right sort of complexity
may yield true understanding. Searles
criticism of strong AIs mind-program
analogyseems justified.
35

• 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.

36

• 5) Qualia
• Qualia raw feels phenomenal experience
  what it is to be like something
• Can a computer have qualia? Again, it is hard to
  tell if/how silicon and metal can have feelings.
  But it is no easier to explain 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?

37

• 6) Searle claims that only biological brains have
  causal relations with the outside world such as
  perception, action, understanding, learning, and
  other intentional phenomena. (Intentionality is
  by definition that featureof certain mental
  states by which they are directed ator about
  objects and states of affairs in the world.)
• However, an AI
• embodied in a robot that puts syntax at use in
  the world as in 4)
• may not need (subjective) Qualia as in 5)
• to permit it perception, action,
  understanding, and learning in the objective
  world.

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Optional Readings for next week

• Sterelny, Kim, The Representational Theory of
  Mind, Section 1.3, pgs. 11-17
• Sterelny, Kim, The Representational Theory of
  Mind, Section 3.1-3.4, pgs. 42-49
• The Representational Theory of Mind. - book
  review by Paul Noordhof, Mind, July,
  1993.http//findarticles.com/p/articles/mi_m2346/
  is_/ai_14330173

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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
• Churchland, Paul, and Patricia Smith Churchland
  (1990) Could a machine think? in Scientific
  American 262, pgs. 26-31
• 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
• http//www3.hku.hk/philodep/joelau/wiki/pmwiki.ph
  p?nMain.Pinker-HowTheMindWorks