From the course conference on ConferU for Gödel, Escher, Bach, Winter Term 1994.
Item 23    Feb03/94 01:27     1 line     41 responses
Paul                          Prime=22
Class of Wed 2/2

 Class of Wed 2/2

   41 responses
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Feb03/94 01:29
23:1)  Paul :
 (I'll post my notes tomorrow; I'm rather tired at the moment.  But I
 thought I'd go ahead and start the item in case people wanted to start
 up discussion on any of the subjects covered.  I myself will give my
 "10-sentence history of AI" at some point. :-)
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Feb03/94 15:51
23:2)  Paul :
 Notes from class of Wed 2/2:

 * signups for presentations
 * read to the end of Part 1 of GEB

 * Questions:
    "God" in GEB
    Bach's last piece (p. 80)
    The "record players" example... JL doesn't think it works too well

 * Chapter 6 (p. 158)
   Recall, H. views language entirely as a written medium
   Bizarre; speech predates writing by far.  50,000 yrs?  500,000?
     Note: speech made possible by a right angle bend in the throat
     (goes with bipedalism)
       Animals and language? discussion
       brood parasite birds; subspecies use "foreign language" as mating call
     Human language&culture are Lamarckian (pass on acquired characteristics)
     Why changes so fast
       Great Vowel Shift (between Chaucer and Shakespeare)
       modern English spelling is Middle English
       pronunciation of long vowels (take twice as long to pronounce) "raised"
       why this sort of language change?  SOME kind of adaptive purpose
   H. equates a lot of things too facilely (math, language, art, music)
   but that doesn't invalidate what he has to say; just, some bits are
   "obiter dictum" (on the path of saying) and not key

   MEANING = core of thought.  A *tough* term to handle!
   one of Bateson's dormitive principles... v. hard to pin down
   property of the human mind
     etymology of "meaning":
     mean (n.) = average <- Lat. medianus (middle)
     mean (adj.) = nasty; comMON; vulgar (class discrimination!)
       note: kind (~king), gentle (~gentleman) originally = upper class
   * mean (v.) = intend <- Lat. mentus (mental, mind)
       Many words are for language/communication
       Also many for people-stuff
         "right" and "left" ... fun to watch a dictionary falter!
         example: chair with doors to hymnal cabinet
         "right arm" (sitting orientation) is not same side as "right door"
         (turn around and get in front to open it)
         "sinister" and "dextrous" --- the minority thing again
     definitions vs. mnemonics vs. determiners ("ways to find out")
   So... meaning is mental, interpretative
   A big question is how does one figure out conventions
   H. has an odd use of "meaning", seems to equate to isomorphic; tho iso.
   is a part of meaning, it's not the same thing (e.g. "phenotype is the
   meaning of the genotype" seems odd; it's the *expression* of it)
   Note that ATCG is a language but not a *human* language.  There is no
   *meaning* in the way we think of it.

   Back to the CONDUIT METAPHOR for communication, from Lakoff & Johnson
     (myths = satisfying explanations picked up as we go along; "age 3")
   1. words & meanings are physical
   2. words are hollow containers.  inside a word is the meaning
   3. communication = sending words physically thru a conduit
     note "code" metaphor for language... implies that there is a code book.
     Where does the code book come from?
   We make up our own internal languages.  Then, we cope.
   Miller: To understand, assume it's true.  Then figure out what it's true
   *of*.  Context is not given.
   Language understanding is "AI-complete"... to do language fully would
    require doing everything else in AI fully as well.
   Humans are "automatic" processors most of the time.
     Long discussion on AI, simulating the brain
     "Can computers learn language?"
     What do you mean by 'learn' & 'language'?
     Chess computers work v. differently from real grandmasters
     (brute force look-ahead, rate moves via heuristics vs.
     "see things", "see what is good", very little conscious search)
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Feb03/94 16:03
23:5)  Mark :
 What notes you take! I relived wed. class all over again. It was nice.
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Feb03/94 16:27
23:6)  Paul :
 OK, here goes, my 10-sentence history of AI!  (OK, so I use a lot of
 semi-colons... :-)

 (1) In the beginning, programmers tried to have computers do the tasks
 that people found "hard", such as playing chess, solving mazes, and
 solving certain kinds of well-defined problems (e.g. the "get the
 wolves and sheep ac the river in a boat" problem).

 (2) Computers got pretty good at these tasks, to the point that modern
 computer chess programs can play at the grandmaster level, although
 they don't work in the same way as human grandmasters (they use
 explicit brute-force "search ahead" through multiple possibilities,
 and rating by heuristics; humans experts use pattern recognition to
 "see patterns, see what to do," with very little conscious

 (3) Meanwhile, a lot of very "easy" things (from a human standpoint)
 turned out to be very tough, such as understanding language and
 recognizing objects; programming using symbols, algorithms, and
 explicit serial rules just doesn't seem to work very well for these
 sorts of tasks, except for very oversimplified problems.

 (4) A fairly recent development (circa 1980) was connectionism
 (parallel distributed processing, neural nets), in which the computer
 works as a parallel "pattern-matcher", trained to recognize certain
 patterns (such as 20 different human faces) and categorize new ones.

 (5) Since the connectionist approach was "inspired by" the complex
 pattern of neurons in the human brain, it's not surprising that it can
 do things via parallel-processing pattern-matching that previously
 could only be done by human brains.

 (6) There are limits to connectionism, however.

(7) So far, connectionist networks can only work at a single level in a
 single domain; some connectionist networks learn to recognize words,
 and other networks form past tenses of verbs, but no one has any idea
 yet how to put these levels together.

 (8) A second problem is that, in current connectionist models,
 programmers still have to specify the symbols by which input and output
 information is coded; the computer itself can't do that.

 (9) My opinion is that future progress in AI will come primarily by
 modeling the human brain even *more* closely, in all its complexity;
 however, the necessary increase in complexity is *enormous*, and there
 is a *lot* that we don't yet know about the brain.  (10) It will
 probably also turn out that modeling just the *brain* isn't enough--
 learning probably has to be done *experientially*, which requires
 perceptual/motor senses, abilities, and interactions...  currently we
 don't have a *clue* as to how to build such a complex entity!
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Feb03/94 17:07
23:8)  Greg :
 I wonder how useful a computer with human reasoning would be.  As you
 already mentioned, human and computers are better at different things.
 Perhaps some other, unconcieved form of intelligence might be more
 usefull.  Besides, we already know how to create human intelligence.  It
 just takes a little teamwork.
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Feb03/94 17:18
23:9)  Perry :
 Greg, I've wondered the same thing, but retain a scientific curiousity
 about whether it can be done...even though I feel no emotional investment
 in it.  Why did we go to the moon?  Because it was there, we wanted to see
 if we could!  Why do we want to recreate the human brain with machinery?
 Because someone asked the question about whether it could be done...and
 maybe we'll learn some interg stuff along the way.
    For me, though, I'll spend my life working with real humans, not the
 silicon approximations!
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Feb03/94 17:29
23:10)  Steven :
 A note on chess, since it's one of my interests:
 Human experts are capable of a great deal of look ahead, and use
 it frequently, in situations where the possibilities are limited,
 such as mating combinations.
 Machines do use *rating by heuristics*, but it isn't clear that an
 adaptive heuristic rating scheme is incapable of "seeing what to
 do" at least as well as a pattern recognition routine.  In fact,
 pattern recognition can be programmed in serial machines, and
 could be used to define an adaptive heuristic.
 I don't know if anyone's working on this or not, but it seems like
 they should be.
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Feb03/94 17:49
23:11)  Steven :
 As far as the "why AI" question, I don't think there's much of
 a push right now to reinvent the human brain.  But we stand to
 learn tons about neurophysiology if we can do experiments on
 brain-like circuits.  Furthermore, there are a lot of industrial
 applications for AI machines, one of the first and foremost is
 robotics control.  AI visual recognition techniques can allow a
 machine entity to find a bolt, orient it correctly, and put it
 in place without human intervention.  You can squawk all you want
 to about displacing human workers, but if the bolt is inside a
 nuclear reactor, or any other hazardous environment, I'll let the
 machine do it, thanks.  If anyone wants to hear more on this
 subject, or ask questions, I'm happy to go on until my keyboard
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Feb04/94 00:55
23:12)  Paul :
 I should point out that my "ten-sentence history of AI" is rather
 biased toward a cognitive psychology viewpoint.  We cogpsych people
 aren't actually very concerned with building intelligent machines,
 except insofar as computer modeling teaches us more about how human
 brains and minds work.  (How we do this is a separate thread which
 I'll skip for now.)

 Most AI researchers are a whole lot more concerned with developing a
 machine that does a particular job, any way that works!  The problem
 is that sometimes our intuitions as to what will work in order to do a
 given job (like recognizing objects or understanding language) are
 *wrong*... in those cases, often the only way to make progress is to
 get inspiration from examining the only working model we have, the
 human brain.

 Computers do some things *better* than humans, though.  Fast
 calculations.  Indexed search through memory.  Following repetitive
 routines without getting bored.  Following a decision-making procedure
 in a consistent way.  (Often, a computerized "expert system" is better
 than the expert it was built to simulate.  Why?  Because it can be
 more *consistent* in applying its algorithms than the human expert

 The *real* problem is how to make computers do tasks they currently
 can't do (by making them more like human brains) *without* losing the
 advantages of current computer design.  For some tasks, like the
 industrial visual scanning that Steve refers to, that may be enough.
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Feb04/94 00:55
23:13)  Paul :
 For other jobs, perhaps the best we can do is to build a machine that
 runs identically to a human brain, but faster; that would be worth
 *something*.  But it would be nice to have even more improvement than

 Steve, re: chess... I was thinking of the middle game more than the
 opening (where both human and computer chessplayers tend to work
 semi-automatically) or the endgame (where the possibilities are
 limited and so both use mostly look-ahead).  Even so, you're right
 that the computer and human aren't quite so qualitatively different as
 I've been describing them.  The more that adaptive the heuristics
 employed by the computer are made, and the more that the "look-ahead"
 is restricted via heuristics to promising patterns, the less
 distinction there is between the human and computer.  But there are
 decreasing marginal gains from *redesigning* meta-heuristics upon
 heuristics... at some point, to get further improvement, it may be
 easier to start with a fresh type of design.  Exactly what, I'm not
 sure... perhaps something like John Holland's adaptive systems notion.
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Feb04/94 14:50
23:14)  Steven :
 Can you give me a reference on Holland?
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Feb04/94 16:02
23:15)  Paul :
 L.B. Booker, D.E. Goldberg and J.H. Holland
 "Classifier Systems and Genetic Algorithms"
 Artificial Intelligence 40 (1989) 235-282

 (Holland's teaching a class this semester, in fact, but it's at 8 AM,
 a time of day at which my brain does not function.)
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Feb04/94 16:11
23:16)  Steven :
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Feb04/94 19:38
23:17)  John Lawler:
 There's also an article in Scientific American recently.  Consult
 Reader's Guide.
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Feb05/94 15:53
23:18)  Jeff :
 "Artificial Intelligence is the study of how to make computers do things at
 which , at the moment, people are better."
                    -Elaine Rich
 Does this seem correct to you?
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Feb06/94 14:29
23:19)  Keenan:
 No quite because it could also be the study of how to make computers out-
 perform other computers.  Or how to just advance the "things" as whole items.
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Feb06/94 16:23
23:20)  Paul :
 Part of the reason Elaine Rich's quote works so well, though, is that
 we keep redefining what we would consider an "intelligent" computer.
 So, for example, once upon a time, doing fast calculations made a
 person "smart", but we don't consider a computer to be smart just
 because it does such quick calculations.

 There's a funny phenomenon by which a somewhat convincing example of
 intelligence (many people can be fooled by a simple Eliza program) is
 no longer considered to be that interg, once one understands how
 the program works.  Kind of like the mathematician who takes 20
 minutes to work out a proof and then decides, "Yes, it *is* obvious!"
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Feb06/94 23:36
23:21)  John Lawler:
 The first sentence of Weizenbaum's paper on Eliza makes that point:
  "It is said that to explain is to explain away."
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Feb09/94 16:29
23:22)  Fran :
 On a prophetic note, I figure that once computers are advanced enough to
 think, really think, they'll start thinking about themselves.  The
 conclusion the computers will come up with is that there is no reason for
 their existence, and having no morals like we humans do, they'll destroy
 themselves.  It's like Frankenstein...

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Feb09/94 19:50
23:23)  Greg :
 Oh yeah, maybe they'll realize that there is no reason for YOUR existance
 and destroy YOU.
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Feb10/94 15:20
23:24)  Fran :
 Be nice Greg, or I'll sic my computer on you.

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Feb10/94 16:20
23:25)! HAL:
 I'm sorry, David. This mission is much too important to jeopardize by
 allowing you back in the ship.
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Feb10/94 17:45
23:26)  Steven :
 Fran: If you believe morals are hard-wired in humans, don't you suppose
 that we can pre-program them in machines?  For example, if we developed
 morals circuitry through evolution (all the immoral humans got offed in
 the inquisition, no? :-) ) couldn't the same sort of biological pressure
 be brought to bear artifically on thinking machines?  All we'd have to do
 is unplug machines that commit immoral acts (like engaging in networking
 with multiple partners).
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Feb11/94 00:00
23:27)  Fran :
 Humans have a moral code, but it's not hard wired.  We can be bad if we
 want to...  It would probably be pretty hard to program freewill...

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Feb11/94 12:54
23:28)  Karen :
 But Fran, how can you say that it is "not hard wired" if you think
 that everyone has it (even if they  choose at times to ignore it?
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Feb11/94 15:54
23:29)  Fran :
 I guess this all depends on what we define as hard wired... This moral
 code that I am talking about is not just one aspect of our psyche that you
 can point to and say, this is it... It's more like a compass that tells
 you what is right at what time.  You can't just pick one human emotion and
 set it up as what is right.  Even someting like love of humanity can bad.
 If you follow love of humanity blindly, you will find yourself breaking
 promises, lying, and falsifying evidence all for humanity's sake and you
 will end up being an unjust person.  There are no right keys and wrong
 keys on a piano, but each one is right at one time and wrong at another.
 The moral code is like sheet music.

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Feb12/94 15:17
23:30)  Jeff :
 "Hard wiring" is normally used in cases where something won't be changing,
 so I'd probably say that moral code is inherent to human nature, rather than
 'hard wired'.
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Feb12/94 19:37
23:31)  Alex :
 That's exactly what Wilson says, Fran and Jeff, and I think I greatly agree
 with you..except I keep wondering..if a moral sense is inherent but weak
 enough to be changed and overruled in every case (i.e. learning morals from
 parents) what difference does it make if its inherent or not?
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Feb13/94 19:22
23:32)  Perry :
 Maybe a *predisposition* to learning/accepting a moral code?...
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Feb13/94 21:52
23:33)  John Lawler:
 How about an "instinct" for a moral code?  Or a set of dormitive
 moral principles?  Or -- this one's very modern -- a moral code
 acquisition device?
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Feb13/94 23:30
23:34)  Brian :
 i kinda of agree with Professor Lawler.  I see it, though, as people
 just like to make general rules of thumb for everything because
 its makes life artificially comprehensible.  parents are there
 just to make the morals good ones.
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Feb14/94 09:16
23:35)  Perry :
 only if the PARENTS are good ones!
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Feb14/94 16:34
23:36)  Steven :
 I'm glad we got off on a new tangent, I kept expecting someone to type
 "the fruit of the tree of the knowledege of good and evil," or somesuch.
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Feb14/94 19:00
23:37)  Paul :
 "Hard-wired" often confuses two ideas, (1) not subject to change, and
 (2) built-in and innate.  In actual human beings, we get all
 combinations.  The pull-hand-out-of-fire reflex is both innate and
 usually unchangeable.  The fear-of-falling reflex is built-in but can
 be changed.  A native language is not innate (though the *ability* to
 learn a language is innate), but once it's learned, much of it is not
 subject to change (see 'phonemic perception' over in item #6).  And
 lots of things are both non-innate and subject to change.

 Morality?  I'd guess that it's like language in some ways, that we
 have a predisposition to learn *some* system.  But just as "language"
 combines a lot of different levels and concepts and stages, so does
 morality.  Some psychologist (I've forgotten the name) talked about
 "stages of morality", ranging from simple avoidance of punishment to
 advocacy of a higher good.  That's probably a good point-- just
 because someone doesn't kill someone, for example, we don't know if
 they really believe that "it is wrong to kill another human being" or
 if they're just afraid of going to jail.  The multiple levels make the
 whole issue really confusing.
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Feb14/94 22:41
23:38)  Perry :
 or if they're too stupid to think of it, or if they're not strong
 enough, or if they just don't feel like it today...
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Feb15/94 19:56
23:39)  Keenan:
 I think that we have to accept some things as true or have some set of
 assumptions because without those it would be very difficult to re-analyze
 every situation that we are put into.  We look at parents to guide out
 behavior so that we don't have to go out and try every possibility.  It would
 make life very interg if every time we were presented with a new
 situation we thought about EVERY possible explaination and choice to be made.
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Feb16/94 18:25
23:40)  Michelle :
 It would slow a lot of things down a lot but it sure would help avoid
 getting stuck in ruts
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Feb16/94 18:31
23:41)  Steven :
 The rut would be having to reexamine discarded possibilities again and
 again and ...

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