Artificial intelligence PHILOSOPHY OF ARTIFICIAL INTELLIGENCE. Strong AI Thesis. Weak AI Thesis. Can a machine think?

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1 Artificial intelligence PHILOSOPHY OF ARTIFICIAL INTELLIGENCE Prof.Dr John-Jules Meyer Dr Menno Lievers 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 2 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?! 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?! 3 4 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 or being intelligent by displaying cognitive activity The Turing Test A human A communicates by 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 5 6

2 The Turing Test Set-Up C B 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?!! A 7 8 Objections against the Turing Test 1. Chimpanzee objection: chimpanzees, dolphins,... will not pass the Turing Test, while they are obviously 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. 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!?! 9 10 Conclusion?! 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 humanlike way of thinking, think also of hypothetical aliens (or animals ) 11 12

3 What is thinking / intelligence? thinking is an intentional notion, it has goal/actiondirected; 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 nontraditional matters such as extraterrestrial intelligence, animals, computers / machines (artificial intelligence) "robots are able to think" may then be a sensible statement 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 storedprogram computer): symbol manipulator operating by executing fundamental operations, such as branch, delete, output, input, compare, shift, write, copy is a 'massively adaptable' machine 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 GOFAI recipe for an IS 1. Use a sufficiently expressive, inductively defined, compositional language to represent 'real-world' objects, 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 GOFAI recipe for an IS 4. Employ complex sequences of the fundamental operations 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 The SSH says: In this way a thinking (= massively adaptable) machine is obtained! 17 18

4 Doubts about the SSH How can such a machine really understand? Or wonder whether a sentence is true? or desire something?... Etc. 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 original GPS project has more or less failed, and modern AI is not yet sufficiently convincing(?!) Philosophical (analytical) considerations (Searle) 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. 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") Searle s Gedankenexperiment The Chinese room 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. Text with questions in Chinese Sam Answers in Chinese 23 Suppose we have a computer program Sam capable to answer questions in Chinese about Chinese texts 24

5 The Chinese room The Chinese room Text with questions in Chinese Joe Answers in Chinese Replace computer program Sam by human Joe executing the program instructions 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 of 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.! 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..." 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. the SSH is FALSE! 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! 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! 29 30

6 The Chinese room revisited And the debate goes on Text with questions In Chinese Joe Answers in Chinese 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!!! 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? 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? 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? 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? 37 38

7 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? 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? 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? 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? 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? 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? 43 44

8 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 nonalgorithmic? Do mathematical theorems like Gödel s show that computers are intrinsically limited? 45

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