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Re: [bafuture] Re: Long post on:Immortality, Singularity, Religiosity, & Zen

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  • Kevin Keck
    @#$%&! That wasn t how it appeared in the so-called preview . (One guess how soon I ll use the Yahoo! Groups web posting form again.) This one should come out
    Message 1 of 21 , Apr 24, 2004
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      @#$%&! That wasn't how it appeared in the so-called
      "preview". (One guess how soon I'll use the Yahoo!
      Groups web posting form again.)

      This one should come out properly:


      I haven't gotten back to this religion thread because
      I've been swamped, not because I didn't have anything
      else to add.

      If you go back and look, some of you might be
      surprised to realize that I did not in fact profess to
      be on either side of the "science is just another
      religion" debate, because in fact I'm not on either
      side. I do appreciate Chris Phoenix's exuberant
      confirmation of my up to that point thinly supported
      assertions about one of the common stances, and I hope
      he won't attribute too malicious an intent to my
      deliberately delayed confession of sympathy for both
      viewpoints.

      The problem, as it is so often, is that the sides are
      talking right past eachother. Of course it's not
      really true that science is just another belief
      system, and it is true that some of the people on the
      other side of academia mean to flatly deny this. But
      there is another contingent which will concede that
      science is in fact a more sophisticated and
      theoretically distinguished belief system, while still
      insisting that this distinction is not very
      significant. And their point is much more than just
      that scientific "knowledge" is always by definition
      both contingent and incomplete�the much bigger point
      is that much of our "reality", including particularly
      most of the morally and politically important aspects
      of it, are socially constructed, and thus in a much
      more profound sense our reality really is _not_
      objective.

      Ironically, in fact, the more advanced our scientific
      and technological knowledge become, the less and less
      relevant it becomes to moral and political issues.
      While on the one hand technology often seems to take
      issues out of the hands of legislators, by
      distributing capabilities to such an extent as to make
      them beyond governmental control, and on the other
      hand it produces issues the political system and
      culture are ill-prepared to deal with, both of these
      are merely the immediate, incremental effects. The
      overarching broader effect is to successively remove
      scientific and technological constraints on the range
      of feasible political, economic, cultural systems
      people can adopt, thereby putting a progressively
      greater demand on our collective capacity for
      imagination, courage, and discretion in order to
      successfully determine and follow wise paths, rather
      than go down very dystopian ones.

      Stewart Brand made a similar observation in his book,
      "How Buildings Learn"�the most successfully adaptable
      buildings turn out to be those with constraints, such
      as support columns, which greatly reduce the "design
      space" which can be considered when contemplating
      modifications. (Perhaps professional architects could
      do more with less constraints, but most building
      dwellers are not architects themselves, so apparently
      less quite often turns out to be more.) I think many
      video game critics (and some movie critics) have also
      similarly suggested that games (or movies) were better
      back when designers (or directors) couldn't fall back
      on eye-popping graphics (or stunts & f/x, or sex and
      violence) to keep players (audiences) entertained. And
      Jaron Lanier is one among several who's voiced the
      opinion that while the capabilities of software have
      in fact gone up as hardware has improved, it has not
      maintained the same pace of improvement, largely
      because the quality of the _code_ has at the same time
      gone very much downhill.

      This doesn't bode well for our ability to "cope", as
      it were, with the continually expanding possibilities
      that accelerating scientific and technological
      progress will continue to bring us. JFK observed that
      we had the power to eliminate hunger in the world back
      in the '60s, and yet it still hasn't happened. Instead
      our politicians spend their time, for example,
      facilitating ever greater abuse of increasingly
      counter-productive IP laws to hinder all kinds of
      things from online music sharing to the provision of
      patented drugs to third world patients. Both are due
      not to technological constraints but rather to
      political ones. I don't want to preach to the choir so
      I'll stop there, but I'm sure all of you have at least
      a couple of other widely-recognized problems which
      come to your mind, which society is either failing to
      address or is continuing to itself cause because of
      "political constraints".

      On a related theme, "Mark L."'s musings on the likely
      nature of a native or innate philosophy in AIs
      actually made something click for me though, in a
      moment of tiredness when I let my guard down enough to
      truly consider it. One of the memes Jaron Lanier puts
      forward in his Half a Manifesto is "cybernetic
      totalism", which is basically the digerati version of
      George Soros's "market fundamentalism" schtick. It's
      also a fair definition of the philosophy that could I
      think fairly be considered the obvious
      pre-disposition, if there is any, of any A.I. system.
      It is essentially a perfection of the reductionist
      hypothesis, holding that not only is reductionism
      valid, but that perception _is_ reality, and that
      recognizing this "fact" is essential to true
      understanding and sound moral judgment. The problem,
      of course, is it's exactly the same type of
      ends-trump-means philosophy which produced the
      devastating seduction of much of the world by nazism,
      fascism, and despotic communism last century. This
      philosophy _is_ dangerous, to an even greater extent
      than Lanier tried to explain.

      Fortunately (for my own sanity), I'm still in the John
      Holland camp (as he articulated it at the 2000
      Stanford "Spiritual Robots" debate, shortly after the
      publication of Bill Joy's infamous Wired article), and
      don't believe the emergence of A.I. will be nearly as
      automatic, inevitable, nor early as Kurzweil an
      company expect, so I'm not terribly worried about it.
      Barring, of course, the frightening possibility of
      Lanier's inversion hypothesis being validated, and
      producing a perceived success by moving the goalposts.
      If we let this happen, then we will in fact create our
      own dystopia, but only by (at least implicit) choice,
      not due to any force of technological determinism.



      I'll try to elaborate my thoughts on Zen and the
      self-other dichotomy soon as well.
      --
      Kevin D. Keck
    • Chris Phoenix
      For another approach to the problem of science, rationality, and the real world, I encourage anyone following this discussion to read my recent Extropy-chat
      Message 2 of 21 , Apr 24, 2004
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        For another approach to the problem of science, rationality, and the
        real world, I encourage anyone following this discussion to read my
        recent Extropy-chat post:
        http://www.lucifer.com/pipermail/extropy-chat/2004-April/005790.html

        I begin by talking about rationality, building a case that the validity
        of thoughts must be considered within their particular context. Usually,
        the context is only within our heads, but we have the cognitive error of
        believing that it extends much farther. If someone else's thought makes
        no sense, it's probably because their context is different. Likewise,
        your thoughts, however rational, are generally unlikely to be
        trustworthy if applied too widely.

        Then I discuss the consistent real world, and how it exists but we have
        trouble addressing it even with science. I'll quote myself rather than
        trying to restate:

        "It's tempting to think that the world is a single context that
        everything can be compared to. But this is equivalent to reductionism.
        There are lots of things in the world that can be understood far more
        completely by approximation than by first principles. For example,
        human psychology has some really weird phenomena (phobias, optical
        illusions, passive-aggressive behavior, etc) that a study of physics
        will not help you understand. To a psychoanalyst or a politician, or
        even a medical doctor, a study of shamanism will have more concrete
        utility than a study of electromagnetism.

        In fact, when dealing with people, not studying at all--not trying to
        form postulates and practice formal thought, but just going on instinct,
        intuition, and experience--may be more effective. This is because
        people are incredibly complex, and we have a strong evolved non-rational
        toolset to help us deal with them. In addition to people, things like
        ecology may still be too complex for rational thought to improve on
        accumulated heuristics, because we simply don't yet know the postulates
        and methods. And then there are things like immunology and cosmology
        where none of our tools really work yet, so the only way to approach
        them is by study and rationality. Eventually, we can expect that study
        and rationality will encompass psychology (including religion and
        parapsychology) and ecology and everything else as well.

        You mentioned the undesirability of chaos. The alternative to chaos is
        the belief that a self-consistent real-world context exists. But even
        though it exists, we can't access it directly. Science is motivated by
        the desire to build conceptual contexts that map to the real-world one.
        Its methods include cataloging (an underrated skill these days),
        categorization, experiment, creativity, criticism, and more. In some
        sub-contexts like electromagnetism, scientists have been very
        successful; the mapping is very close. In protein folding, the end is
        in sight. Pedagogy, psychology, and oncology are quagmires, though
        oncology may be ready for a synthesis.

        But back to the practice of science: the trouble is that scientists,
        like everyone else, are prone to the illusion that their chosen context
        extends everywhere. Let's be clear: I don't mean that scientists should
        leave room for the paranormal or magical. They should not. I mean that
        chemists should leave room for physics, and physicists should leave room
        for psychology, and psychologists should leave room for chemistry.
        Otherwise you get absurdities like chemists declaring that Drexler's
        physics and mechanics work is worthless, when it's obvious they don't
        even understand it.

        One thing I never see addressed in discussions of rationality: How does
        a rational thinker know when to keep their ears open and their mouth
        shut? Obviously, the belief that a rational thinker will be an expert
        in everything is irrational. But it's far too common. Scientists are
        slowly learning enough to be rational in certain limited contexts. And
        in a few glorious areas, those contexts have spread enough to merge.
        But anyone who aspires to rationality should learn from the
        overconfidence of scientists who, secure in their rationality, talk
        nonsense outside their field. That's as big a mistake--I would argue
        that it's the same mistake--as religious people talking nonsense while
        feeling secure in their irrationality. The mistake is assuming that
        their mental context extends farther than it actually does.

        And scientists and rationalists have even less excuse than
        irrationalists. If as great a scientist as Lord Kelvin could be wrong
        about something as mundane and technical as heavier-than-air flight,
        surely the rest of us should be extremely cautious when talking outside
        our field of study--or even inside it, for many fields. But no, we keep
        making the same mistake: our context defines our universe, and
        everything we see must be made to conform. Appeals to rational thought,
        in the end, are usually just another way to rationalize this process."

        Chris

        Ps. Note the very awkward formatting of your post; please correct that.

        Pps. I should have cited a source in the Extropy-chat article: the
        mundane explanation for the "loaves and fishes miracle" comes from a
        book called "The Robe."

        Kevin D. Keck wrote:

        > I haven't gotten back to this religion thread because I've been
        swamped, no=
        >
        > t because I didn't have anything else to add.
        >
        > If you go back and look, some of you might be surprised to realize
        that I d=
        >
        > id not in fact profess to be on either side of the "science is just
        another religion" deba=


        --
        Chris Phoenix cphoenix@...
        Director of Research
        Center for Responsible Nanotechnology http://CRNano.org
      • J. Andrew Rogers
        ... It is probably worth pointing out that one can prove this mathematically for algorithmically finite systems (which includes a subset of non-finite state
        Message 3 of 21 , Apr 24, 2004
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          On Apr 24, 2004, at 12:41 PM, Chris Phoenix wrote:
          > I begin by talking about rationality, building a case that the validity
          > of thoughts must be considered within their particular context.
          > Usually,
          > the context is only within our heads, but we have the cognitive error
          > of
          > believing that it extends much farther. If someone else's thought
          > makes
          > no sense, it's probably because their context is different. Likewise,
          > your thoughts, however rational, are generally unlikely to be
          > trustworthy if applied too widely.


          It is probably worth pointing out that one can prove this
          mathematically for algorithmically finite systems (which includes a
          subset of non-finite state machines in addition to all finite state
          machines). In fact, the mathematical expression of this is one of the
          more useful theorems of algorithmic information theory. An interesting
          theoretical direction of this is that one can compute the limits of
          correctness for a particular model in a particular context (the
          "predictive limit" of a finite model).

          Or to put it in simpler terms: In any finite subcontext, rationality
          does not imply correctness, and correctness does not imply rationality.
          But it is theoretically possible to compute the maximum probability
          that a rational model is also a correct model. For some arbitrary
          brain/machine, the actual probability will be of the form:

          0 < x < predictive limit < 1

          where "x" is the actual probability that some rational model is correct
          in some context, and the predictive limit is the maximum theoretical
          probability that a model might be correct in that context. Why there
          is often a significant difference between "x" and the predictive limit
          for intelligent systems is a complex topic that I'll simply avoid.

          Humans have an extremely poor grasp of the predictive limits of the
          model of the universe that they build in their brains. Not only are
          many (most?) people unaware that rationality does not imply
          correctness, just about everyone is oblivious to the predictive limits
          of their rationality with respect to correctness. There are many
          things in the universe that can only be modeled to such low predictive
          limits in the human brain that one would have to be skeptical of any
          claim as to the correctness of those models.

          j. andrew rogers
        • Chris Phoenix
          You mean there s theoretical justification for what I said? Cool! Is it thought to extend to systems that are not algorithmically finite as well? What about
          Message 4 of 21 , Apr 24, 2004
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            You mean there's theoretical justification for what I said? Cool! Is
            it thought to extend to systems that are not algorithmically finite as
            well? What about algorithmic approximations to non-A.F. systems? Can
            you give me a reference or two for this?

            Chris

            J. Andrew Rogers wrote:

            > On Apr 24, 2004, at 12:41 PM, Chris Phoenix wrote:
            >
            >>I begin by talking about rationality, building a case that the validity
            >>of thoughts must be considered within their particular context.
            >>Usually,
            >>the context is only within our heads, but we have the cognitive error
            >>of
            >>believing that it extends much farther. If someone else's thought
            >>makes
            >>no sense, it's probably because their context is different. Likewise,
            >>your thoughts, however rational, are generally unlikely to be
            >>trustworthy if applied too widely.
            >
            >
            >
            > It is probably worth pointing out that one can prove this
            > mathematically for algorithmically finite systems (which includes a
            > subset of non-finite state machines in addition to all finite state
            > machines). In fact, the mathematical expression of this is one of the
            > more useful theorems of algorithmic information theory. An interesting
            > theoretical direction of this is that one can compute the limits of
            > correctness for a particular model in a particular context (the
            > "predictive limit" of a finite model).
            >
            > Or to put it in simpler terms: In any finite subcontext, rationality
            > does not imply correctness, and correctness does not imply rationality.
            > But it is theoretically possible to compute the maximum probability
            > that a rational model is also a correct model. For some arbitrary
            > brain/machine, the actual probability will be of the form:
            >
            > 0 < x < predictive limit < 1
            >
            > where "x" is the actual probability that some rational model is correct
            > in some context, and the predictive limit is the maximum theoretical
            > probability that a model might be correct in that context. Why there
            > is often a significant difference between "x" and the predictive limit
            > for intelligent systems is a complex topic that I'll simply avoid.
            >
            > Humans have an extremely poor grasp of the predictive limits of the
            > model of the universe that they build in their brains. Not only are
            > many (most?) people unaware that rationality does not imply
            > correctness, just about everyone is oblivious to the predictive limits
            > of their rationality with respect to correctness. There are many
            > things in the universe that can only be modeled to such low predictive
            > limits in the human brain that one would have to be skeptical of any
            > claim as to the correctness of those models.
            >
            > j. andrew rogers
            >
            >
            >
            >
            > Yahoo! Groups Links
            >
            >
            >
            >
            >

            --
            Chris Phoenix cphoenix@...
            Director of Research
            Center for Responsible Nanotechnology http://CRNano.org
          • J. Andrew Rogers
            ... It is only true for algorithmically finite cases, but since this seems to cover all likely real spaces, you get a lot of bang for that buck as a
            Message 5 of 21 , Apr 25, 2004
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              On Apr 24, 2004, at 2:44 PM, Chris Phoenix wrote:
              > You mean there's theoretical justification for what I said? Cool! Is
              > it thought to extend to systems that are not algorithmically finite as
              > well? What about algorithmic approximations to non-A.F. systems? Can
              > you give me a reference or two for this?


              It is only true for algorithmically finite cases, but since this seems
              to cover all likely "real" spaces, you get a lot of bang for that buck
              as a pragmatic matter. In terms of references, they are sparse but
              what you are looking for is probably "non-axiomatic reasoning systems",
              and Pei Wang's work in this area is probably the best and most
              accessible on the Internet. There has been an interesting bit of
              activity over the last year or two toward the unification of the fields
              of probability theory, information theory, computational theory,
              reasoning/logics, and a couple other bits and pieces as different
              facets of a single elegant universal conceptual model for
              algorithmically finite systems. My theoretical point comes from some
              of the bridgework that is unifying reasoning logics and algorithmic
              information theory. There isn't a lot out there; the first mentions of
              this general result is implied in some papers from the early '90s on
              universal predictors and Pei Wang's stuff, but we've really only worked
              it all out in the last couple years (and is still a work in progress).

              Finite versus Infinite mathematics:

              Algorithmically infinite systems are actually the standard assumption
              for classic theory in these areas, and it is of limited utility. That
              is how you end up with things like standard first-order logics. The
              problem is that we missed a lot because of this. Some very interesting
              things emerge when you restrict the mathematics purely to the finite
              case, often in areas that were considered mathematically "undefined" in
              the general case (mostly because the inclusion of infinite parameters
              force an undefined value for theorems and functions that have rich,
              interesting, and definable properties when restricted to purely finite
              parameters).

              As for what "algorithmically finite" means:

              The classic "finite state" is an inadequate system descriptor for the
              above area of mathematics, and the term "algorithmically finite"
              denotes something distinct from "finite state", though there are
              conceptual similarities. I actually coined the distinction a couple
              years ago. I used to regularly argue with a math-savvy retired
              Christian lady about the nature of religion and God in a mathematical
              context -- I've developed a lot of good pure theory angles in the
              course of trying to prove mathematical points to her, best exercise of
              theory I ever got. She made the poignant observation that the apparent
              algorithmic finiteness of the universe did not seem to have any obvious
              dependency on the universe actually being a finite state machine in the
              classical sense. And she seemed to have a point after I thought about
              it for a bit, which I later formalized.


              "Algorithmically finite" means (very roughly) a system that can only
              express finite intrinsic Kolmogorov complexity in finite time. A
              properly rigorous definition is fairly difficult to express well, and
              tonight is not that night. Interesting things that fall out of this
              are:

              1.) This is inclusive of all finite state systems.
              2.) The effective Kolmogorov complexity of these systems can vary in
              time.
              3.) This is inclusive of some infinite state systems.

              The second property looks mundane, but is actually relatively
              interesting. This essentially replaces an important given constant in
              classic computational theory with a function. Since expressible
              intelligence also varies with Kolmogorov complexity, this has
              interesting implications. It is worth noting that this can also break
              the assumptions of some theorems from classic theory.

              The third property is interesting in that you can have infinite state
              systems that are mathematically bound to express the computational
              properties of finite systems over any finite span of time. An example
              of such a system would be a system with a countably infinite state
              fabric (say, at the resolution of the Planck length) and a finite bound
              on information propagation (say, the speed of light), resulting in a
              system which would be mathematically required to do things like express
              an analog of the Laws of Thermodynamics that falls out of algorithmic
              information theory. While such a system is nominally infinite state,
              it is theoretically limited to the expression of finite algorithms with
              a Kolmogorov complexity limit that varies in finite time.

              From a functional standpoint, I would say that the AF model is more
              general than the classic finite state machine model.

              Okay, its past my bedtime,

              j. andrew rogers
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