Artificial intelligence Artificial Intelligence is the science of - - PDF document

SLIDE 1

1

PHILOSOPHY OF ARTIFICIAL INTELLIGENCE

Prof.Dr John-Jules Meyer Dr Menno Lievers

2

Artificial intelligence

• “Artificial Intelligence is the science of

making machines do things that would require intelligence if done by men”

Marvin Minsky – Weak AI thesis – Strong AI thesis

3

Weak AI Thesis

• The computer is (only) a powerful aiding

tool for the study of the human mind

• It is possible to construct machines that

perform useful “intelligent” tasks assisting human users

– Difficult enough?!

4

Strong AI Thesis

• An adequately programmed computer has a

cognitive state - computer programs explain human cognition

• It is possible to devise machines that behave

like people and possess human capabilities, such as the ability to think, reason, ..., play chess, walk, ..., have emotions, pain, ...

– possible?? – desirable?!

5

Can a machine think?

• Try to first answer the question ‘in principle’,

independent of available technology

• Is consciousness necessary for thinking?

– Human mental processes are often non-conscious

• 'sleeping problem solver'
• 'blindsight'
• You

may replace ‘thinking’

• r

‘being intelligent’ by ’displaying cognitive activity’

6

The Turing Test

• A human A communicates by email

with a human B and a computer C

• A poses questions to both B and C to

discover which is the human

• If A doesn’t succeed to distinguish B

and C, the computer C passes the Turing Test

SLIDE 2

2

7

The Turing Test Set-Up

A B C

8

Has the Turing Test been passed already?

• Turing test: based on link between ’thinking' en

'conversation'

• Two famous ‘conversation’ programs:

– ELIZA – PARRY

• ELIZA and PARRY are based on relatively simple

pattern matching algoritms: this is not thinking…?!!

9

Objections against the Turing Test

1. Chimpanzee objection: chimpanzees, dolphins, ... will not pass the Turing Test, while they are

• bviously intelligent and able to think! So a negative

result does not say anything about being able to think / being intelligent. 2. sensory versus verbal communication: the TT only concerns verbal communication: no test of the computer’s ability to relate words to things in the world.

10

Objections against the Turing Test

• 3. simulation objection: simulated X ≠ X. This objection

says that thinking cannot ever be simulated perfectly

• 4. Black Box objection: the external behaviours are

equal does not imply that the processes are themselves equal!

 SUPERPARRY: program containing all conversations of length ≤100 words: is finite in principle and programmable; will pass the Turing test; however, does not think !?!

11

Conclusion?!

12

Can we improve the Turing Test ?

• In any case we need the following

criteria:

– Output criterion: competition between two ‘agents’ – Design criterion: it is not about the human- like way

• f

thinking, think also

• f

hypothetical aliens (or animals…)

SLIDE 3

3

13

What is thinking / intelligence?

• thinking is an intentional notion, it has goal/action-

directed; it has to do with explaining and predicting of behaviour −−−> planning, being flexible, adaptable

• Generalise this notion: it is about being 'massively

adaptable' → this notion is applicable to non- traditional matters such as extraterrestrial intelligence, animals, computers / machines (artificial intelligence) ∴ "robots are able to think" may then be a sensible statement

14

Symbol System Hypothesis

• thinking = 'being massively adaptable'
• Is this achievable using digital computers?

– I.o.w. if we can make machines ‘think’, is a digital computer the right kind of machine?

• symbol system hypothesis (SSH): yes!:

– a universal symbol system (= general-purpose stored- program computer): symbol manipulator operating by executing fundamental operations, such as branch, delete,

• utput, input, compare, shift, write, copy is a 'massively

adaptable' machine

15

Intelligent systems

• An intelligent ('massively adaptable’) system (IS)

should be able to:

– Generate plans – Analyze situations – Deliberate decisions – Reason and revise 'beliefs' – Use analogies – Weigh conflicts of interest, preferences – Decide rationally on the basis of imperfect information – Learn, categorize

16

GOFAI recipe for an IS

• 1. Use a sufficiently expressive, inductively defined,

compositional language to represent 'real-world'

• bjects, events, actions, relations, etc.
• 2. Construct an adequate representation of the

world and the processes in it in a universal symbol system (USS) : extensive Knowledge Base (KB)

• 3. Use suitable input devices to obtain symbolic

representation of environmental stimuli

17

GOFAI recipe for an IS

• 4. Employ complex sequences of the fundamental
• perations of the USS to be applied to the

symbol structures of the inputs and the KB, yielding new symbol structures (some of these are designated as output)

• 5. This output is a symbolic representation of

response to the input. A suitable robot body can be used to ‘translate’ the symbols into real behaviour / action

18

• The SSH says:
• In this way a thinking (= massively adaptable)

machine is obtained!

SLIDE 4

4

19

Doubts about the SSH

• How can such a machine really understand?
• Or wonder whether a sentence is true?
• or desire something?
• ... Etc.

20

Status SSH

• the SSH is an interesting conjecture, that may

appear strange, but may be true after all (there are more strange things that are held to be true: e.g. relativity theory, quantum mechanics...); however:

– Is there any evidence by the state of the art in AI?:

• Not (yet): all AI at the moment is rather limited; the
• riginal GPS project has more or less failed, and modern

AI is not yet sufficiently convincing(?!)

– Philosophical (analytical) considerations (Searle)

21

Strong Symbol System Hypothesis (SSSH)

• SSH:

computers (i.e.. univ. symbol manipulators) can think

• SSSH:

ONLY computers (univ. symbol manipulators) can think, i.e. the only things capable of thinking are univ. symb. manip.; ergo, the human mind is a univ. symb. manip., a computer!!!

– The SSSH is even more controversial than the SSH.

22

Philosophical objections against Strong AI & SSH: Searle

• Is the question whether a computer is suitable device

for thinking an empirical one?

• Searle: the question whether a symbol manipulating

device can think is not empirical, but analytical, and can be answered negatively :

– a universal symbol manipulator (USS) operates purely syntactically and is not able to really understand what it is doing! – syntax is insufficient for dealing with semantics (= "understanding of what symbols actually mean")

23

Searle’s Gedankenexperiment

• John Searle tries to argue by means of a

Gedankenexperiment that a computer cannot think, or more precisely, cannot perform an intelligent task, such as e.g. answer questions in Chinese about a Chinese text, and really understand what it is doing.

24

The Chinese room

Text with questions in Chinese Answers in Chinese Sam

Suppose we have a computer program Sam capable to answer questions in Chinese about Chinese texts ダソまめキずそぜゑわボ

SLIDE 5

5

25

The Chinese room

Text with questions in Chinese Answers in Chinese Joe

Replace computer program Sam by human Joe executing the program instructions ダソまめキずそぜゑわボ

26

The Chinese room

• Chinese room argument:

– Joe in the room executing the computer program Sam manually, does not understand the story nor the questions, nor the answers: only manipulation

• f meaningless symbols: "Sam 'run' on a human

computer" – Executing the program does not enable Joe to understand the story, questions, etc., ergo executing the program does not enable the computer to understand the story, questions etc. !

27

Chinese room: Searle’s conclusion

• running

a program does not lead to understanding, believing, intending, thinking …!

• "merely manipulating symbols will not enable

the manipulating device to understand X, believe Y, think Z..." ∴ the SSH is FALSE !

28

But …?!?

• But… cannot we ‘prove’ in the same way

that humans (i.e. our brains) cannot think …?!?

– Let the global population (5 billion people) simulate a brain B with its 100 billion neurons: then each person controls some 20 neurons – No person knows what B is thinking… – So, neither do(es) (the neurons in) brain B.

29

The “Systems Reply”

• 'The systems reply': Not only the symbol

manipulator Joe is concerned but the system as a whole: it could be possible that the whole system does understand!

30

Counter-objection

• Searle contra de systems reply:

1. Joe does not understand, but Joe + paper + pencil would understand ?!? (cynically) 2. Let Joe learn all rules of the program by heart; then there is no ‘bigger’ system any more of which Joe is part; in fact everything is part of Joe in that case!

SLIDE 6

6

31

The Chinese room revisited

Text with questions In Chinese Answers in Chinese Joe

ダソまめキずそぜゑわボ

32

And the debate goes on…

• Searle:

− SSH ⇒ 'toilet paper' machine (= TM) thinks as well ?!?! − biological objection to the SSH and AI

• Copeland:

− although Joe may say of himself that he does not understand, an external observer may still say that Joe does understand!!!

35

The Great Debates in AI

• Can computers think?
• Can the Turing Test determine whether computers

can think?

• Can physical symbol systems think?
• Can Chinese Rooms think?
• Can connectionist networks think? Can computers

think in images?

• Do computers have to be conscious to think?
• Are thinking computers mathematically possible?

36

Can computers think?

• Is the brain a computer?
• Can computers have free will?
• Can computers have emotions?
• Can computers be creative?
• Should we pretend computers will

never be able to think?

37

Can computers think?

• Does God prohibit computers from

thinking?

• Can computers understand arithmetic?
• Can computers draw analogies?
• Are computers inherently disabled?
• Can computers reason scientifically?
• Can computers be persons?

38

Can the TT determine whether computers can think?

• If a simulated intelligence passes,

is it intelligent?

• Does the imitation game determine

whether computers can think?

• Is passing / failing the test decisive?
• Have any machines passed the test?
• Is the test a legitimate intelligence

test?

SLIDE 7

7

39

Can Physical Symbol Systems Think?

• Can the elements of thinking be

represented in symbolic form?

• Can physical symbol systems learn as

humans do?

• Do humans use rules as physical symbol

systems do?

• Can a symbolic knowledge base represent

human understanding?

• Can symbolic representations account for

human thought?

40

Can Physical Symbol Systems Think?

• Does thinking require a body?
• Can physical symbol systems think

dialectically?

• Is the relation between hardware and

software similar to that between human brains and minds?

• Does mental processing rely on heuristic

search?

• Do physical symbol systems play chess as

humans do?

41

Can Chinese Rooms Think?

• Can the Chinese Room, considered as a

total system, think?

• Can an internalized Chinese Room

think?

• Can brain simulators think?
• Can robots think?
• Do Chinese Rooms instantiate programs?
• Can computers cross the syntax-semantics

barrier?

42

Can Connectionist Networks Think?

• Are connectionist networks

vulnerable to the arguments against physical symbol systems?

• Do connectionist networks follow

rules?

• Does the subsymbolic account offer

a valid account of connectionism?

43

Can Computers Think in Images?

• Can images be realistically represented

in computer arrays?

• Can computers recognize Gestalts?
• Are images less fundamental than

propositions?

• Is image psychology a valid approach to

mental processing?

• Can computers represent the analogue

properties of images?

44

Do Computers Have to Be Conscious to Think?

• Can computers be conscious?
• Is consciousness necessary for thought?
• Is the consciousness requirement

solipsistic?

• Can functional states generate

consciousness?

• Can higher-order representations

produce consciousness?

SLIDE 8

8

45

Are Thinking Computers Mathematically Possible?

• Can automata think?
• Does Gödel’s theorem show that machines

can’t think / can’t be conscious?

• Does Gödel’s theorem show that

mathematical insight is non- algorithmic?

• Do mathematical theorems like Gödel’s

show that computers are intrinsically limited?