Re: [bafuture] Re: Long post on:Immortality, Singularity, Religiosity, & Zen
- @#$%&! 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
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_
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
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
- 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:
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."
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 beenswamped, no=
>that I d=
> t because I didn't have anything else to add.
> If you go back and look, some of you might be surprised to realize
>another religion" deba=
> id not in fact profess to be on either side of the "science is just
Chris Phoenix cphoenix@...
Director of Research
Center for Responsible Nanotechnology http://CRNano.org
- On Apr 24, 2004, at 12:41 PM, Chris Phoenix wrote:
> I begin by talking about rationality, building a case that the validityIt is probably worth pointing out that one can prove this
> of thoughts must be considered within their particular context.
> the context is only within our heads, but we have the cognitive error
> believing that it extends much farther. If someone else's thought
> 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.
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
- 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?
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.
>>the context is only within our heads, but we have the cognitive error
>>believing that it extends much farther. If someone else's thought
>>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
- On Apr 24, 2004, at 2:44 PM, Chris Phoenix wrote:
> You mean there's theoretical justification for what I said? Cool! IsIt is only true for algorithmically finite cases, but since this seems
> 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?
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
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
1.) This is inclusive of all finite state systems.
2.) The effective Kolmogorov complexity of these systems can vary in
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