Com1005 Machines and Com1005 Machines and IntelligenceIntelligence

Lecturers: Dr Amanda Sharkey, Lecturers: Dr Amanda Sharkey, Professor Phil GreenProfessor Phil Green

Lecture 1: What is Artificial Lecture 1: What is Artificial Intelligence?Intelligence?

• ““Artificial Intelligence (AI) is the Artificial Intelligence (AI) is the study of intelligent behaviour (in study of intelligent behaviour (in humans, animals and machines) and humans, animals and machines) and the attempt to find ways in which the attempt to find ways in which such behaviour could be engineered such behaviour could be engineered in any type of artifact” (Whitby, in any type of artifact” (Whitby, 2003)2003)

Varying defintionsVarying defintions

• John McCarthyJohn McCarthy, “It is the science and engineering , “It is the science and engineering of making intelligent machines, especially intelligent of making intelligent machines, especially intelligent computer programs.”computer programs.”

• Herbert Simon: Herbert Simon: We call programs intelligent if they We call programs intelligent if they exhibit behaviours that would be regarded intelligent exhibit behaviours that would be regarded intelligent if they were exhibited by human beings. if they were exhibited by human beings.

• Elaine Rich (1991) “Elaine Rich (1991) “AI is the study of how to make AI is the study of how to make computers do things at which, at the moment, computers do things at which, at the moment, people are better.” people are better.”

• Astro TeAstro Telller:ler: AI is the attempt to make computers AI is the attempt to make computers do what they do in the movies. do what they do in the movies.

Main themes of this Main themes of this semester semester Artificial Intelligence – overview of progressArtificial Intelligence – overview of progress- Different approaches to creating intelligent behaviourDifferent approaches to creating intelligent behaviour

- Computationalism .... Mind as computerComputationalism .... Mind as computer

- Brain-like (Artificial Neural Nets)Brain-like (Artificial Neural Nets)

- Brain, body and world (Embodied AI)Brain, body and world (Embodied AI)

- Different goalsDifferent goals- Understanding and simulating intelligenceUnderstanding and simulating intelligence

- Applied AIApplied AI

- Creating the illusion of intelligenceCreating the illusion of intelligence

Artificial Intelligence programming: search, planning and Artificial Intelligence programming: search, planning and knowledge representationknowledge representation

• LecturesLectures

• ““Guru” lectures – AI research in the Guru” lectures – AI research in the departmentdepartment

• Assessment over the year: Assessment over the year: – written assignment (this semester), written assignment (this semester), – Group presentation (this semester), Group presentation (this semester), – practical assignment (next semester)practical assignment (next semester)– exam for whole year (next semester).exam for whole year (next semester).

Origins of AI and early history Origins of AI and early history of digital computerof digital computer

• 1941 Germany: Konrad Zuse, Z3 first general purpose 1941 Germany: Konrad Zuse, Z3 first general purpose programmable computerprogrammable computer

Colossus – 10 delivered to Bletchley Park. Colossus – 10 delivered to Bletchley Park. Designed by British engineer Tommy Designed by British engineer Tommy Flowers to break Nazi codes.Flowers to break Nazi codes.

ENIAC (1945) electronic computer rewired by hand ENIAC (1945) electronic computer rewired by hand for each task.for each task.

Manchester Mark 1 computer: 1948. General Manchester Mark 1 computer: 1948. General purpose computer with stored programs. purpose computer with stored programs.

Punched Punched paper paper tape tape for for new new jobjob

AI: Where did it all begin?AI: Where did it all begin?

• 1956 Dartmouth Summer Research Project1956 Dartmouth Summer Research Project– month long ‘brain storming’ sessionmonth long ‘brain storming’ session– Attendees: John McCarthy (Father of AI, inventor of Attendees: John McCarthy (Father of AI, inventor of

LISP). Invented term “artificial intelligence”LISP). Invented term “artificial intelligence”– Also Allen Newell, Herbert Simon, Marvin Minsky, Oliver Also Allen Newell, Herbert Simon, Marvin Minsky, Oliver

Selfridge, Claude Shannon and othersSelfridge, Claude Shannon and others

– Idea that “every aspect of learning, or any other Idea that “every aspect of learning, or any other feature of intelligence can in principle be so precisely feature of intelligence can in principle be so precisely described that a machine can be made to simulate it”described that a machine can be made to simulate it”

What is Artificial Intelligence?What is Artificial Intelligence?

• Attempt to Attempt to understandunderstand intelligent intelligent entitiesentities

• Attempt to Attempt to build build intelligent entitiesintelligent entities

• Attempt to create the Attempt to create the appearance appearance of of intelligenceintelligence

Understanding intelligent Understanding intelligent entitiesentities

• Can computers be intelligent? Can computers be intelligent?

• Or is intelligence unique to humans, Or is intelligence unique to humans, or to living beings?or to living beings?

• Can we use computers to help us Can we use computers to help us understand how we think?understand how we think?

John Searle:John Searle:

• Strong AIStrong AI: an appropriately : an appropriately programmed computer really is a programmed computer really is a mind, can be said to understand, and mind, can be said to understand, and has other cognitive states.has other cognitive states.

• Weak AIWeak AI: a computer is a valuable : a computer is a valuable tool for study of mind – makes it tool for study of mind – makes it possible to formulate and test possible to formulate and test hypotheses rigorouslyhypotheses rigorously

• Ray Kurzweil: “The singularity is Ray Kurzweil: “The singularity is near”near”

• Strong AI .... Artificial intelligence Strong AI .... Artificial intelligence that matches or exceeds human that matches or exceeds human intelligenceintelligence

• Artificial general intelligenceArtificial general intelligence

• Artificial narrow intelligenceArtificial narrow intelligence

Building intelligent Building intelligent machinesmachines• Designing programs to perform tasks Designing programs to perform tasks

intelligentlyintelligently

• Should computer programs think like Should computer programs think like humans?humans?

• Should they be programmed to Should they be programmed to operate like human brains?operate like human brains?

• Should they exploit different Should they exploit different strengths?strengths?

Creating the appearance of Creating the appearance of intelligenceintelligence

What is intelligence?What is intelligence?

Can psychology help?Can psychology help?• 1921 Journal of Educational Psychology asked 14 1921 Journal of Educational Psychology asked 14

experts for definitionsexperts for definitions• 14 different definitions including14 different definitions including

– The ability to carry on abstract thinking (Terman)The ability to carry on abstract thinking (Terman)– The ability to adapt oneself adequately to relatively new The ability to adapt oneself adequately to relatively new

situations in life (Pintner)situations in life (Pintner)– The capacity to acquire capacity (Woodrow) The capacity to acquire capacity (Woodrow) – The capacity to learn or profit by experience (Dearborn)The capacity to learn or profit by experience (Dearborn)

• ““few concepts in psychology have received more few concepts in psychology have received more devoted attention and few have resisted devoted attention and few have resisted clarification so thoroughly” (Reber, 1995)clarification so thoroughly” (Reber, 1995)

Intelligence in humansIntelligence in humans

• What is intelligence? What is intelligence?

• Intelligence is what is measured by Intelligence is what is measured by intelligence testsintelligence tests..

• IQ intelligence quotient IQ intelligence quotient – Based on abstract reasoning abilityBased on abstract reasoning ability

• 1915 Stanford-Binet test- 1915 Stanford-Binet test- • Objective measure, aims – to identify those Objective measure, aims – to identify those

children who need specialised, simplified children who need specialised, simplified educationeducation

• Uses concept of mental age versus chronological Uses concept of mental age versus chronological ageage

• Items in test age graded- mental age corresponds Items in test age graded- mental age corresponds to level achieved in test.to level achieved in test.

• Eg. A 4 year old should be able to complete the Eg. A 4 year old should be able to complete the following:following:

• Brother is a boy; Sister is a ……Brother is a boy; Sister is a ……Bright child – mental age above chronological age.Bright child – mental age above chronological age.

• Adult versions developed and Adult versions developed and standardized.standardized.

• Weschler developed test for adults Weschler developed test for adults and proposed Gaussian distribution and proposed Gaussian distribution of resultsof results

• 2/3 should be between 85 and 115, 2/3 should be between 85 and 115, (100 mean) and 2.3% above 130 and (100 mean) and 2.3% above 130 and below 70.below 70.

• Single factor, or multiple intelligences?Single factor, or multiple intelligences?• Spearman, single factor g underlying Spearman, single factor g underlying

intelligence.intelligence.• Gardner – multiple intelligencesGardner – multiple intelligences• Linguistic, musical, logical-mathematical, Linguistic, musical, logical-mathematical,

spatial, bodily-kinesthetic, personalspatial, bodily-kinesthetic, personal• But strong correlations between But strong correlations between

performance in different areas – single performance in different areas – single underlying factor of intelligence?underlying factor of intelligence?

• Correlations of .4 and .6 between Correlations of .4 and .6 between school grades and Wechsler IQ test.school grades and Wechsler IQ test.

• Correlation with university results Correlation with university results lowerlower

• Correlation with job performance .51 Correlation with job performance .51 (Hunter and Schmidt 1998)(Hunter and Schmidt 1998)

• Problems: Problems: – Difficult to find items which are independent of Difficult to find items which are independent of

culture and educationculture and education• E.g. pick odd wordE.g. pick odd word• cello harp drum violin guitarcello harp drum violin guitar• Rich kids picked drum, poor kids celloRich kids picked drum, poor kids cello

• Also IQ tests don’t measureAlso IQ tests don’t measure– CreativityCreativity– MotivationMotivation– Most geniuses also work very hard (e.g Mozart Most geniuses also work very hard (e.g Mozart

and practice)and practice)

• Robert Sternberg (2003)Robert Sternberg (2003)

• Triarchic theory of intelligenceTriarchic theory of intelligence• 1. Analytical intelligence1. Analytical intelligence, the ability to complete , the ability to complete

academic, problem-solving tasks, such as those used in academic, problem-solving tasks, such as those used in traditional intelligence tests. These types of tasks usually traditional intelligence tests. These types of tasks usually present well-defined problems that have only a single present well-defined problems that have only a single

correct answercorrect answer..• 2. Creative or synthetic intelligence2. Creative or synthetic intelligence, the ability to , the ability to

successfully deal with new and unusual situations by successfully deal with new and unusual situations by drawing on existing drawing on existing knowledge and and skills. Individuals high in . Individuals high in creative intelligence may give 'wrong' answers because creative intelligence may give 'wrong' answers because they see things from a different perspective.they see things from a different perspective.

• 3. Practical intelligence3. Practical intelligence, the ability to adapt to everyday , the ability to adapt to everyday life by drawing on existing knowledge and skills. Practical life by drawing on existing knowledge and skills. Practical intelligence enables an individual to understand what needs intelligence enables an individual to understand what needs to be done in a specific setting and then do it.to be done in a specific setting and then do it.

• Machines and IQ tests?Machines and IQ tests?

Intelligence and machines?Intelligence and machines?

The Turing TestThe Turing Test

• Outside appearances used to judge Outside appearances used to judge intelligenceintelligence

• Turing, A. (1950) Computing machinery Turing, A. (1950) Computing machinery and intelligence, Mind, 59, 433-460.and intelligence, Mind, 59, 433-460.

• I propose to consider the question ‘Can I propose to consider the question ‘Can machines think?’machines think?’

• When paper written, only 4 electronic When paper written, only 4 electronic computers in existence, and it was before computers in existence, and it was before Dartmouth conference and ‘birth’ of AIDartmouth conference and ‘birth’ of AI

Turing testTuring test

Turing testTuring test

• Like Victorian parlour game. I interrogator, 1 woman, Like Victorian parlour game. I interrogator, 1 woman, 1 man1 man

• 1 interrogator, 1 person, 1 computer1 interrogator, 1 person, 1 computer• Interrogator can ask any questionsInterrogator can ask any questions• Human must be truthful (trying to help the Human must be truthful (trying to help the

interrogator), computer can try to force wrong interrogator), computer can try to force wrong identificationidentification

• Experiment repeated with a range of people in 2 Experiment repeated with a range of people in 2 human positions. Test passed if number of successful human positions. Test passed if number of successful identifications of computer is less than 30%identifications of computer is less than 30%

• Machine can lie – e.g. if asked if it has ever written a Machine can lie – e.g. if asked if it has ever written a poem it could say it has, and it could pretend to get poem it could say it has, and it could pretend to get calculations wrong.calculations wrong.

PredictionsPredictions

• 1950 Turing: “I believe that in about fifty years' time it will be 1950 Turing: “I believe that in about fifty years' time it will be possible to programme computers, with a storage capacity of possible to programme computers, with a storage capacity of about 10about 1099, to make them play the imitation game so well that , to make them play the imitation game so well that an average interrogator will not have more than 70 percent an average interrogator will not have more than 70 percent chance of making the right identification after five minutes of chance of making the right identification after five minutes of questioning. … I believe that at the end of the century the use questioning. … I believe that at the end of the century the use of words and general educated opinion will have altered so of words and general educated opinion will have altered so much that one will be able to speak of machines thinking much that one will be able to speak of machines thinking without expecting to be contradicted.”without expecting to be contradicted.”

• 1965, Herbert Simon predicted that “machines will be capable, 1965, Herbert Simon predicted that “machines will be capable, within twenty years, of doing any work that a man can do”. within twenty years, of doing any work that a man can do”.

• 1967 Marvin Minsky “within a generation… few compartments 1967 Marvin Minsky “within a generation… few compartments of intellect will remain outside the machine’s realm” of intellect will remain outside the machine’s realm”

ELIZAELIZA

• Weizenbaum, J. (1965) ELIZA – a Weizenbaum, J. (1965) ELIZA – a computer program for the study of computer program for the study of natural language communication natural language communication between man and machine. between man and machine. Communications of the Association Communications of the Association for Computing Machinery, 9(1) 36-45.for Computing Machinery, 9(1) 36-45.

• Therapeutic interview with a teenagerTherapeutic interview with a teenager• Men are all alikeMen are all alike• IN WHAT WAY?IN WHAT WAY?• They’re always bugging us about something or They’re always bugging us about something or

other.other.• CAN YOU THINK OF A SPECIFIC EXAMPLE?CAN YOU THINK OF A SPECIFIC EXAMPLE?• Well my boyfriend made me come hereWell my boyfriend made me come here• YOUR BOYFRIEND MADE YOU COME HERE?YOUR BOYFRIEND MADE YOU COME HERE?• He says I’m depressed much of the timeHe says I’m depressed much of the time• I AM SORRY TO HEAR THAT YOU ARE I AM SORRY TO HEAR THAT YOU ARE

DEPRESSEDDEPRESSED• It’s true that I am unhappyIt’s true that I am unhappy• DO YOU THINK COMING HERE WILL HELP YOU DO YOU THINK COMING HERE WILL HELP YOU

NOT TO BE UNHAPPY?NOT TO BE UNHAPPY?• I need some help, that much seems certain.I need some help, that much seems certain.• WHAT WOULD IT MEAN TO Y0U IF YOU GOT WHAT WOULD IT MEAN TO Y0U IF YOU GOT

SOME HELP?SOME HELP?

• Perhaps I could learn to get along with my Perhaps I could learn to get along with my mother.mother.

• TELL ME MORE ABOUT YOUR FAMILYTELL ME MORE ABOUT YOUR FAMILY• My mother takes care of meMy mother takes care of me• WHO ELSE IN YOUR FAMILY TAKES CARE OF WHO ELSE IN YOUR FAMILY TAKES CARE OF

YOU?YOU?• My fatherMy father• YOUR FATHERYOUR FATHER• You are like my father in some waysYou are like my father in some ways• WHAT RESEMBLANCE DO YOU SEE?WHAT RESEMBLANCE DO YOU SEE?• You are not very aggressive, but I think you You are not very aggressive, but I think you

don’t want me to notice that.don’t want me to notice that.• WHAT MAKES YOU THINK I AM NOT VERY WHAT MAKES YOU THINK I AM NOT VERY

AGGRESSIVE?AGGRESSIVE?• You don’t argue with meYou don’t argue with me• WHY DO YOU THINK I DON’T ARGUE WITH YOU?WHY DO YOU THINK I DON’T ARGUE WITH YOU?• You are afraid of meYou are afraid of me

• DOES IT PLEASE YOU TO BELIEVIE DOES IT PLEASE YOU TO BELIEVIE I AM AFRAID OF YOU?I AM AFRAID OF YOU?

• My father is afraid of everybodyMy father is afraid of everybody

• WHAT ELSE COMES TO MIND WHAT ELSE COMES TO MIND WHEN YOU THINK OF YOUR WHEN YOU THINK OF YOUR FATHER?FATHER?

• BulliesBullies

• DOES THAT HAVE ANYTHING TO DOES THAT HAVE ANYTHING TO DO WITH THE FACT THAT YOUR DO WITH THE FACT THAT YOUR BOYFRIEND MADE YOU COME BOYFRIEND MADE YOU COME HERE?HERE?

Has the test been passed Has the test been passed already?already?

• Business executive and ElizaBusiness executive and Eliza• Do you think that I can use the computer this morning?Do you think that I can use the computer this morning?• WHY DO YOU ASK?WHY DO YOU ASK?• I might be able to make some additional Telcomp sales.I might be able to make some additional Telcomp sales.• WHY AREN’T YOU SURE?WHY AREN’T YOU SURE?• My prospective customers have never seen a demonstration of the My prospective customers have never seen a demonstration of the

systemsystem• DOES THIS MEAN VERY MUCH TO YOU?DOES THIS MEAN VERY MUCH TO YOU?• Of course it does.Of course it does.• YOU SEEM VERY POSITIVE ABOUT THATYOU SEEM VERY POSITIVE ABOUT THAT• This is ridiculousThis is ridiculous• WHAT DO YOU MEAN THIS IS RIDICULOUS?WHAT DO YOU MEAN THIS IS RIDICULOUS?• Is there any reason why I can’t use the computer now?Is there any reason why I can’t use the computer now?• TELL ME MORE ABOUT YOUR PROSPECTIVE CUSTOMERSTELL ME MORE ABOUT YOUR PROSPECTIVE CUSTOMERS

Parry the paranoid program.Parry the paranoid program.Colby, K.M., Weber, S., Hildf, F.D. (1971) Colby, K.M., Weber, S., Hildf, F.D. (1971) Artificial Paranoia. Artificial Intelligence, 2, 1-Artificial Paranoia. Artificial Intelligence, 2, 1-25.25.• Why are you in the hospital?Why are you in the hospital?• I SHOULDN’T BE HEREI SHOULDN’T BE HERE• Who brought you here?Who brought you here?• THE POLICETHE POLICE• What trouble did you have with the police?What trouble did you have with the police?• COPS DON’T DO THEIR JOBCOPS DON’T DO THEIR JOB• What do they do instead?What do they do instead?• COPS ARREST THE WRONG PEOPLECOPS ARREST THE WRONG PEOPLE• They arrest the right ones sometimes.They arrest the right ones sometimes.• THE LAW SHOULD GET THOSE ITALIAN CROOKSTHE LAW SHOULD GET THOSE ITALIAN CROOKS• Are you Italian?Are you Italian?• MY BACKGROUND IS BRITISH BUT I WAS BORN IN THIS MY BACKGROUND IS BRITISH BUT I WAS BORN IN THIS

COUNTRYCOUNTRY

• Do you know any Italian crooks?Do you know any Italian crooks?• I TRY TO AVOID THE UNDERWORLDI TRY TO AVOID THE UNDERWORLD• Are you afraid of the underworld?Are you afraid of the underworld?• THE MAFIA ARE THE WORST GANGSTERSTHE MAFIA ARE THE WORST GANGSTERS• Are you connected with the Mafia?Are you connected with the Mafia?• YOU KNOW, THEY KNOW MEYOU KNOW, THEY KNOW ME• How do they know you?How do they know you?• THEY SPY ON METHEY SPY ON ME• Why do they?Why do they?• THEY WANT TO GET FALSE EVIDENCE TO FRAME METHEY WANT TO GET FALSE EVIDENCE TO FRAME ME• What do they have against you?What do they have against you?• THEY ARE OUT TO GET METHEY ARE OUT TO GET ME• What for?What for?

• I HAVE INCRIMINATING EVIDENCE AGAINST THE MAFIAI HAVE INCRIMINATING EVIDENCE AGAINST THE MAFIA• Are you sure of all this?Are you sure of all this?• YOU DON’T BELIEVE ME?YOU DON’T BELIEVE ME?• I am doing my best….. I am doing my best….. • SilenceSilence• CAN’T YOU THINK OF A DECENT QUESTION TO ASK ME?CAN’T YOU THINK OF A DECENT QUESTION TO ASK ME?• You seem hostile to meYou seem hostile to me• SOME OF YOUR REMARKS ANNOY MESOME OF YOUR REMARKS ANNOY ME• I am sorryI am sorry• FORGET THE EXCUSES, YOU GUYS ARE ALL ALIKE.FORGET THE EXCUSES, YOU GUYS ARE ALL ALIKE.

Loebner TestLoebner Test

• Competition started 1991 by Hugh LoebnerCompetition started 1991 by Hugh Loebner• Judges type questions on terminal, either human Judges type questions on terminal, either human

or computer repliesor computer replies• Judges rate responses on how human-like they Judges rate responses on how human-like they

appear. $2000 prize to the most human like. appear. $2000 prize to the most human like. $100,000 prize if a program does better than one $100,000 prize if a program does better than one of the humansof the humans

• 2010 competition: 232010 competition: 23rdrd October in LA October in LA• http://www.loebner.net/Prizef/loebner-prize.htmlhttp://www.loebner.net/Prizef/loebner-prize.html• 1997 winner: Intelligent Research Ltd, partly 1997 winner: Intelligent Research Ltd, partly

programmed by our NLP groupprogrammed by our NLP group

2009: “Do-Much-More” 2009: “Do-Much-More” won.... won.... 2009 winner of Loebner Prize: “Do-Much-More”2009 winner of Loebner Prize: “Do-Much-More”

Designed to respond with generalities, moving conversation Designed to respond with generalities, moving conversation along in light hearted way. along in light hearted way.

No specialist knowledge.No specialist knowledge.

• Judge-1: Hi, how is it going? Judge-1: Hi, how is it going?

• Do-Much-More: Hello. How are you doing?Do-Much-More: Hello. How are you doing?

• Judge-1: Good, who are you? Judge-1: Good, who are you?

• Do-Much-More: Well, I am studying engineering. That ought to Do-Much-More: Well, I am studying engineering. That ought to give you an idea about who I am.give you an idea about who I am.

• Judge-1: No, not really? Judge-1: No, not really?

• Do-Much-More: I have a terrific yearning to know something more Do-Much-More: I have a terrific yearning to know something more about experiments?about experiments?

• Judge-1: Where are you from? Judge-1: Where are you from?

• Do-Much-More: I don't know, but don't forget I can't be in three Do-Much-More: I don't know, but don't forget I can't be in three places at once.places at once.

• Judge-1: What lang~~~~city do you live in? Judge-1: What lang~~~~city do you live in?

• Do-Much-More: What city -- that's rather a tricky question. The Do-Much-More: What city -- that's rather a tricky question. The trouble is, one city seems to be much like another.trouble is, one city seems to be much like another.

• Judge-1: Not really. Where do you live? Judge-1: Not really. Where do you live?

• Do-Much-More: In the old dairy next to the river, I believe.Do-Much-More: In the old dairy next to the river, I believe.

• Judge-1: Interesting, so you are a farmer then? Judge-1: Interesting, so you are a farmer then?

• Do-Much-More: Well, if you ask a physiologist what I am, he won't Do-Much-More: Well, if you ask a physiologist what I am, he won't say I'm a farmer. He'll say I consist mostly of water -- enough to fill say I'm a farmer. He'll say I consist mostly of water -- enough to fill a large beer tun -- plus some iron, phosphorus, and lots of other a large beer tun -- plus some iron, phosphorus, and lots of other prosaic ingredients.prosaic ingredients.

• Judge-1: Wie~~eird answer to a simple question, wouldn't yous~ Judge-1: Wie~~eird answer to a simple question, wouldn't yous~ say? say?

Do-Much-More: I certainly would. Just watch me!Do-Much-More: I certainly would. Just watch me!

Judge-1: What will I see? Judge-1: What will I see?

Do-Much-More: You don't have to worry about Do-Much-More: You don't have to worry about what you see, you shouldn't see it on a cold what you see, you shouldn't see it on a cold winter's evening.winter's evening.

Judge-1: What do you make of the Arctic Monkeys? Judge-1: What do you make of the Arctic Monkeys?

Do-Much-More: Well, here's a clue: I make what a Do-Much-More: Well, here's a clue: I make what a keeper in a zoo would make. Try that for sizekeeper in a zoo would make. Try that for size!!

Survey of 21 experts at AGI-09 conference Survey of 21 experts at AGI-09 conference (Baum et al, 2010)(Baum et al, 2010)

SummarySummary

• Birth of AI, and first computersBirth of AI, and first computers• What is intelligence? – history of What is intelligence? – history of

intelligence testingintelligence testing• Turing test – a particular view of what Turing test – a particular view of what

intelligence is. Takes simplifying view that intelligence is. Takes simplifying view that if behaviour of computer is if behaviour of computer is indistinguishable from human, it must be indistinguishable from human, it must be intelligent.intelligent.

• Early conversational programsEarly conversational programs• Loebner testLoebner test