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Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at.

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Presentation on theme: "Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at."— Presentation transcript:

1 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Part I: Introduce you to what’s happening in Artificial Intelligence Part II: Give you an appreciation for the big picture  Why it is a grand challenge Done

2 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Part I: Introduce you to what’s happening in Artificial Intelligence Part II: Give you an appreciation for the big picture  Why it is a grand challenge Done

3 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Looking at the Science  Engineering vs. Science  Introduction to Cognitive Science  Cognitive Psychology 1  Cognitive Psychology 2  Cognitive Development  Linguistics  Neuroscience  Philosophy

4 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Looking at the Science  Engineering vs. Science  Introduction to Cognitive Science  Cognitive Psychology 1  Cognitive Psychology 2  Cognitive Development  Linguistics  Neuroscience  Philosophy

5 Philosophy  “The love of wisdom”  The Father of all disciplines…  When they get more developed they leave philosophy  Age old question: what is mind, thought, consciousness, etc.  AI brings new twist  Tries to understand by building working models  Theories can be tested  “Certum quod factum.”  “Certum quod factum.” (Giambattista Vico, )  We are only certain of what we create or make up ourselves

6 Questions for Philosophy of AI 1.Can a machine do any intellectual task that a human can? (i.e. pass any type of Turing Test) If it does… then… 2.Does the machine then have a mind, mental states and consciousness just like humans do? e.g. Can it feel? 3.Is the human brain essentially a computer?

7 René Descartes ( )  Separated mental and physical  “Cartesian Dualism”  Physical body like a machine  Mind/soul is not material  Does not follow laws of physics  How can one affect other?  Mind  body (controls)  Body  mind (act of passion)  Pineal Gland  allows mind-body interaction  Question he asked: How can physical body be affected by non-physical mind?  Critics would say that mental phenomena are simply physical

8 Gottfried Wilhelm Leibniz ( ) "The only way to rectify our reasonings is to make them as tangible as those of the Mathematicians, so that we can find our error at a glance, and when there are disputes among persons, we can simply say: Let us calculate [calculemus], without further ado, to see who is right."

9 Gottfried Wilhelm Leibniz ( )  Believed that much of human reasoning could be reduced to mathematical calculations  Believed in calculations using symbols  He wanted a symbol for each fundamental concept  Complex concepts would be built by combining fundamentals  Thought of an “algebra of thought”  Developed beginnings of logic  First Computer Scientist?  Invented binary number system  Mechanical calculator “Stepped Reckoner” "It is unworthy of excellent men to lose hours like slaves in the labour of calculation, which could be safely relegated to anyone else if machines were used."

10 Can a Computer Think? "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” - Edsger Dijkstra  Turing proposed imitation game  Advantages:  Up to subject to pick any question/topic  Can test Natural Language, learning, reasoning, etc.  Criticisms  Only tests similarity to human conversation – not really intelligence  Aeronautical engineering doesn ’ t try to build machines to fool pigeons  Mimicry might pass – fool people  Presumes functionalist view – only behaviour matters  Some people disagree i.e. some people think it is necessary to look at the implementation  Can also strengthen test with video input, or object input  Test is essentially about behaviour

11 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

12 Turing’s Arguments  The Theological Objection  Could argue that God could put soul into computer when AI program created  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

13 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  Consequences of machine thinking are awful  Some people like to believe man is superior/special  Rarely expressed openly, but lies behind a lot of arguments  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

14 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  Questions the machine can’t answer  … but humans can’t answer everything either  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

15 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Could never really feel … (not just following rules)  Can apply to other people  forced to solipsist view  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

16 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Cannot fall in love, enjoy strawberries and cream etc.  If shown method by which machine can do it… usually unimpressed  Usually comes back to argument from consciousness  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

17 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection "The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform“  Turing says: do humans really originate anything  Can machines surprise us? Yes  Idea that machines cannot give rise to surprises: Fallacy that people assume all consequences of a fact immediately spring to mind  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

18 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  Nerve signals are continuous, not discrete  Turing says: very easy to mimic behaviour of continuous machine with probabilities for giving different responses  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

19 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  Impossible to set up rules to describe what a man should do in every conceivable set of circumstances  Turing says: there are rules, but could be extremely hard to find  Even simple program, can be hard to find rules based on behaviour  The Argument from Extrasensory Perception

20 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception  Could test machine against a “good telepathic receiver”  Turing says: machine’s random number generator could be affected by psychokinetic powers of the interrogator

21 Turing’s Arguments  The Theological Objection  The "Heads in the Sand" Objection  The Mathematical Objection (Godel's theorem)  The Argument from Consciousness  Arguments from Various Disabilities  Lady Lovelace's Objection  Argument from Continuity in the Nervous System  The Argument from Informality of Behaviour  The Argument from Extrasensory Perception

22 Alan Turing, 1950 “I believe that in about fifty years time it will be possible to programme computers with a storage capacity of about 10 9 to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning.”

23 Searle’s Chinese Room  Imagine a computer in the future  Takes Chinese characters as input  Produces Chinese characters as output  Passes the Turing Test (for Chinese speaker)  Now: Computationalist says:  Computer really is a mind,  Understands and has other cognitive states  Imagine Searle is in a room  Receives Chinese characters  Consults a book containing English version of the computer program  Processes the Chinese characters according to book instructions  Produces answer in Chinese  But he doesn’t understand (Turing’s “Argument from Consciousness”)  Mindless manipulators of symbols

24 Penrose’s Quantum Gravity  Human consciousness cannot be explained by algorithms alone  …Because of halting problem and Gödel's theorem  Proposes human consciousness is the result of quantum gravity effects in microtubules  (mathematical argument, but possibly theological argument also)

25 Penrose’s Quantum Physics Stephen Hawking’s view… “his argument seemed to be that consciousness is a mystery and quantum gravity is another mystery so they must be related. Personally I get uneasy when people, especially theoretical physicists, talk about consciousness. Consciousness is not a quality that we can measure from the outside.... I prefer to talk about intelligence which is a quality that can be measured form the outside.”

26 Hubert Dreyfus's criticism of AI  AI says cognition is manipulation of internal symbols by rules  Possible to find the 'internal' rules of the human mind, in the same way the laws of physics  Dreyfus argues that we cannot know these rules  Human intelligence lies in unconscious instincts (not conscious symbol manipulation)  These unconscious skills can never be captured in rules  Idea of trying to capture unconscious rather than rules could be seen as similar to Rodney Brooks  Recall Turing’s “Argument from Informality of Behaviour”  Rules may be hard to find  …but doesn’t mean there are no rules

27 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Looking at the Science  Engineering vs. Science  Introduction to Cognitive Science  Cognitive Psychology 1  Cognitive Psychology 2  Cognitive Development  Linguistics  Neuroscience  Philosophy

28 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Part I: Introduce you to what’s happening in Artificial Intelligence Part II: Give you an appreciation for the big picture  Why it is a grand challenge Done

29 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Part I: Introduce you to what’s happening in Artificial Intelligence Part II: Give you an appreciation for the big picture  Why it is a grand challenge Done

30 Course Overview  What is AI?  What are the Major Challenges?  What are the Main Techniques?  Where are we failing, and why?  Step back and look at the Science  Step back and look at the History of AI  What are the Major Schools of Thought?  What of the Future? Part I: Introduce you to what’s happening in Artificial Intelligence Part II: Give you an appreciation for the big picture  Why it is a grand challenge Done

31 History: Alan Turing  Interestingly… The family of Turing, originally French, settled in the barony of Tourin, in Forfarshire, which they held for several generations. Sir William TURYN attached himself to the fortunes of King David II., and shared that monarch's exile; his loyalty was however subsequently rewarded by a grant of the barony of Foveran, in Aberdeenshire, which his descendants held more than 300 years. “ The family of Turing, originally French, settled in the barony of Tourin, in Forfarshire, which they held for several generations. Sir William TURYN attached himself to the fortunes of King David II., and shared that monarch's exile; his loyalty was however subsequently rewarded by a grant of the barony of Foveran, in Aberdeenshire, which his descendants held more than 300 years. ” - Debrett's Peerage

32 The Turing Stone  In Foveran, North of Aberdeen see

33 History: Alan Turing  Born 1912 London  Upper-middle-class  Father entered the Indian Civil Service  Parents stayed in India, Turing and older brother fostered in homes in England  Showed early interest in science  Public School was not impressed…

34 Alan Turing at Public School  English: Bottom of the class. "I can forgive his writing, though it is the worst I have ever seen, and I try to view tolerantly his unswerving inexactitude and slipshod, dirty, work, inconsistent though such inexactitude is in a utilitarian; but I cannot forgive the stupidity of his attitude towards sane discussion on the New Testament."  Latin, only second from bottom: "He ought not to be in this form of course as far as form subjects go. He is ludicrously behind."  Maths and science better but… “His work is dirty”

35 Alan Turing at Public School  Headmaster wrote to his parents: “If he is to stay at public school, he must aim at becoming educated. If he is to be solely a Scientific Specialist, he is wasting his time at a Public School.”

36 Alan Turing: School Days  Read about theory of relativity  His notes showed he fully understood  1928 Made friends with Christopher Morcom at school  Morcom died suddenly in 1930  from complications of bovine tuberculosis  Crisis for Turing  Began to think how the human mind was embodied in matter  could it be released from matter by death?

37 Alan Turing at Cambridge  Unwillingness to work on classical studies (only science and mathematics)  Failed to win a scholarship to Trinity College  1931 undergraduate at King's College, Cambridge (2 nd choice)  Won a Prize in 1936 for work on probability theory  Became interested in Hilbert’s Entscheidungsproblem (decision problem) of 1928  1936, Turing came up with proof of impossibility  …but Alonzo Church published independent paper also showing that it is impossible  1937 Turing’s "On computable numbers, with an application to the Entscheidungsproblem“ published

38 Entscheidungsproblem  Interesting the way Turing proved it  Universal Turing Machine – accepts code as input – any operation  Abstract idea:  Code and data are the same  Both just information  Therefore can make a programmable machine  One machine to do anything  Machine maybe more practically useful idea… Even though his original goal was simply to prove theorem  To capture idea of definite method  Bridge between maths and physics (operations of mind)  Considered Founder of Computer Science  At this stage he was not clear about mind being a machine  Maybe intuitive steps were uncomputable?

39 Alan Turing During War  1938 returned to Cambridge  Began secret work for British cryptanalytic department  With declaration of war (Sept. 1939) worked full-time at Bletchley Park  Made Bombe machine – needed portion of correct plaintext  1940 Turing-Welchman Bombe reading Luftwaffe signals  … but German Naval communications were generally regarded as unbreakable  Turing had cracked system, but needed more material to be captured  Regular decryption began in mid-1941  February 1942 Germans added extra step  Eventually cracked (1943) while Turing in USA  Worked on Collosus computers at Bletchley Park  Note: first time computer machines became really important  military technology, governments put money in, saved lives


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