CMSC 471 Fall 2002 - PowerPoint PPT Presentation

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CMSC 471 Fall 2002

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CMSC 471 Fall 2002 Class #10 Wednesday, October 12 Today s class History of AI Key people Significant events Future of AI Where are we going Philosophy of AI ... – PowerPoint PPT presentation

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Title: CMSC 471 Fall 2002


1
CMSC 471Fall 2002
  • Class 10 Wednesday, October 12

2
Todays class
  • History of AI
  • Key people
  • Significant events
  • Future of AI
  • Where are we going
  • Philosophy of AI
  • Can we build intelligent machines?
  • If we do, how will we know theyre intelligent?
  • Should we build intelligent machines?
  • If we do, how should we treat them
  • and how will they treat us?

3
History of AI
  • Chronology of AI Russell Norvig Ch. 26

4
Key people (AI prehistory)
  • George Boole invented propositional logic (1847)
  • Karel Capek coined the term robot (1921)
  • Isaac Asimov wrote many sf books and essays (I,
    Robot (1950) introduced the Laws of Robotics if
    you havent read it, you should!)
  • John von Neumann minimax (1928), computer
    architecture (1945)
  • Alan Turing universal machine (1937), Turing
    test (1950)
  • Norbert Wiener founded the field of cybernetics
    (1940s)
  • Marvin Minsky neural nets (1951), AI founder,
    blocks world, Society of Mind
  • John McCarthy invented Lisp (1958) and coined the
    term AI (1957)
  • Allen Newell, Herbert Simon GPS (1957), AI
    founders
  • Noam Chomsky analytical approach to language
    (1950s)

5
Key people (early AI history)
  • Hubert and Stuart Dreyfus anti-AI specialists
  • Ed Feigenbaum DENDRAL (first expert system,
    1960s)
  • Terry Winograd SHRDLU (blocks world, 1960s)
  • Roger Schank conceptual dependency graphs,
    scripts (1970s)
  • Shakey mobile robot (SRI, 1969)
  • Doug Lenat AM, EURISKO (math discovery, 1970s)
  • Ed Shortliffe, Bruce Buchanan MYCIN (uncertainty
    factors, 1970s)

6
Key events Genesis of AI
  • Turing test, proposed in 1950 and debated ever
    since
  • Neural networks, 1940s and 1950s, among the
    earliest theories of how we might reproduce
    intelligence
  • Logic Theorist and GPS, 1950s, early symbolic AI
  • Dartmouth University summer conference, 1956,
    established AI as a discipline
  • Early years focus on search, learning, knowledge
    representation
  • Development of Lisp, late 1950s

7
Key events Adolescence of AI
  • The movie 2001 A Space Odyssey (1968) brought AI
    to the publics attention
  • Early expert systems DENDRAL, Meta-DENDRAL,
    MYCIN
  • Arthur Samuelss checkers player, Doug Lenats AM
    and EURISKO systems, and Werboss and Rumelharts
    backpropagation algorithm held out hope for the
    ability of AI systems to learn
  • Hype surrounding expert systems led to an
    inevitable decline in interest in the mid to late
    1980s, when it was realized they couldnt do
    everything
  • Hype surrounding neural networks in the late
    1980s led to similar disappointment in the 1990s
  • Roger Schanks conceptual dependency theory and
    Doug Lenats Cyc started to address problems of
    common-sense reasoning and representation
  • Hans Berliners heuristic search player defeated
    the world backgammon champion in 1979

8
Key events AI adulthood (barely)
  • Many commercial expert systems introduced,
    especially in the 1970s and 1980s
  • Fuzzy logic and neural networks used in
    controllers, especially in Japan and Europe
  • Recent developments and areas of great interest
    include
  • Bayesian reasoning and Bayes nets
  • Ontologies, knowledge reuse, and knowledge
    acquisition
  • Mixed-initiative systems that combine the best of
    human and computer reasoning
  • Multi-agent systems, Internet economies,
    intelligent agents
  • Autonomous systems for space exploration, search
    and rescue, hazardous environments

9
Are we there yet?
  • Great strides have been made in knowledge
    representation and decision making
  • Many successful applications have been deployed
    to (help) solve specific problems
  • Key open areas remain
  • Incorporating uncertain reasoning
  • Real-time deliberation and action
  • Perception (including language) and action
    (including speech)
  • Lifelong learning / knowledge acquisition
  • Common-sense knowledge
  • Methodologies for evaluating intelligent systems

10
Philosophy of AI
  • Alan M. Turing, Computing Machinery and
    Intelligence
  • John R. Searle, Minds, Brains, and Programs
  • (also Russell Norvig Ch. 27)

11
Philosophical debates
  • What is AI, really?
  • What does an intelligent system look like?
  • Does an AI needand can it haveemotions,
    consciousness, empathy, love?
  • Can we ever achieve AI, even in principle?
  • How will we know if weve done it?
  • If we can do it, should we?

12
Turing test
  • Basic test
  • Interrogator in one room, human in another,
    system in a third
  • Interrogator asks questions human and system
    answer
  • Interrogator tries to guess which is which
  • If the system wins, its passed the Turing Test
  • The system doesnt have to tell the truth
    (obviously)

13
Turing test objections
  • Objections are basically of two forms
  • No computer will ever be able to pass this test
  • Even if a computer passed this test, it wouldnt
    be intelligent
  • Chinese Room argument (Searle, 1980), responses,
    and counterresponses
  • Robot reply
  • Systems reply

14
Machines cant think
  • Theological objections
  • Its simply not possible, thats all
  • Arguments from incompleteness theorems
  • But people arent complete, are they?
  • Machines cant be conscious or feel emotions
  • Reductionism doesnt really answer the question
    why cant machines be conscious or feel
    emotions??
  • Machines dont have Human Quality X
  • Machines just do what we tell them to do
  • Maybe people just do what their neurons tell them
    to do
  • Machines are digital people are analog

15
The Turing test isnt meaningful
  • Maybe so, but
  • If we dont use the Turing test, what measure
    should we use?
  • Very much an open question

16
Ethical concerns Robot behavior
  • How do we want our intelligent systems to behave?
  • How can we ensure they do so?
  • Asimovs Three Laws of Robotics
  • A robot may not injure a human being or, through
    inaction, allow a human being to come to harm.
  • A robot must obey orders given it by human beings
    except where such orders would conflict with the
    First Law.
  • A robot must protect its own existence as long as
    such protection does not conflict with the First
    or Second Law.

17
Ethical concerns Human behavior
  • Is it morally justified to create intelligent
    systems with these constraints?
  • As a secondary question, would it be possible to
    do so?
  • Should intelligent systems have free will? Can we
    prevent them from having free will??
  • Will intelligent systems have consciousness?
    (Strong AI)
  • If they do, will it drive them insane to be
    constrained by artificial ethics placed on them
    by humans?
  • If intelligent systems develop their own ethics
    and morality, will we like what they come up
    with?
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