Very good, Richard. Agree to great extent. Yes the human mind is a complex,
interdependent system of subsystems, and you can't chop them off.
[Yes BTW to the "insanity", i.e. literally out-of-the-human-mind, nature of
sci. psychology. First, no mind - behaviourism. Then, yes there's a mind,
but only an unconscious mind. Then, 1990's, oh we do have a conscious mind
too. And still we only study consciousness, as a set of faculties, and not
Thought - the conscious mind's actual streams of debate - the geology, if
you like, but not the geography of human thought.].
But what you seem to be missing out is the evolutionary (& developmental)
standpoint. The human mind evolved. And it also has to develop in stages
through childhood, which to a limited extent recapitulates evolution.
So you have to understand why the human system had to evolve and has to
develop in those ways. You can't just attempt to recreate, say, an
already-developed adult human mind by a super-Manhattan project. We're
nowhere near ready for that yet.
(An interesting thought BTW here is that adaptivity itself adapts, becomes
more sophisticated through life - and evolution evolves).
Sure, Ben, AGI does not have to copy the evolution of mind exactly, but
there are basic principles there of constructing a mind that I think do have
to be adhered to, just as there were basic principles of flight..
For example, here nearly everyone seems to be talking about plunging in and
creating a sophisticated intellectual mind more or less straight-off, but it
takes the human brain roughly 13-20 years to develop physically and mentally
to where it is able to intellectualise - to handle concepts like "society"
and "development" and "philosophy." Why? I would argue because those powers
of abstraction have been grounded in gradually building up a picture tree of
underlying images and graphics, of great depth, with extraordinary CGI
powers of manipulating them. An abstract concept, for example, like
"society", I'm suggesting, is based on a lot of images in the brain - and
you have to have them to handle it - as you do all such abstract concepts..
----- Original Message -----
From: "Richard Loosemore" <[EMAIL PROTECTED]>
To: <singularity@v2.listbox.com>
Sent: Wednesday, April 25, 2007 4:59 PM
Subject: [singularity] Re: Why do you think your AGI design will work?
Joshua Fox wrote:
Ben has confidently stated that he believes Novamente will work (
http://www.kurzweilai.net/meme/frame.html?m=3
<http://www.kurzweilai.net/meme/frame.html?m=3> and others).
AGI builders, what evidence do you have that your design will work?
This is an oft-repeated question, but I'd like to focus on two possible
bases for saying that an invention will work before it does.
1. A clear, simple, mathematical theory, verified by experiment. The
experiments can be "pure science" rather than technology tests.
2. Functional tests of component parts or of crude prototypes.
Maybe I am missing something in the articles I have read, but do
contemporary AGI builders have a verified theory and/or verified
components and prototypes?
Joshua,
I happen to think your question is a very important one. I am writing a
paper on something very close to that question right now, so I want to
summarize what I have said there.
First of all, I think a lot of the replies to your post went off at a
tangent: inventing a test means nothing (no matter how much fun it is) if
the justification for the test is nonexistent. It doesn't matter how many
tests people pull out of thin air, the whole point of your question was
WHY should we believe this or that test, or WHY should we believe this or
that definition of intelligence, or WHY should we believe this or that
design for an AGI is better than any other.
What we need is the BASIS that anyone might have for asserting the
superiority of one answer over another .... except personal judgment.
But:
This 'basis' is completely missing from all of AI research. AI is just
one great big free-for-all exploration, based on personal judgements that
are often kept away from the limelight, to build something that works as
well as human intelligence. There are no principled approaches, there are
only hidden assumptions/preconceptions/guesses, on top of which are
layered various kinds of formalism that are designed to make it look more
scientific. (And if it seems outrageous to say that so many people are
being so self-deceiptful, take a quick look at the history of behaviorism,
in psychology.... very similar story, same conclusion).
The above is meant to be a position statement: I believe that I can
justify it by means of a long essay, with lots of evidence, but let's just
take it for granted right now, so I can move on to the next step.
Here is what I think is happening.
1) Everyone is actually borrowing crucial ideas from the design of the
human cognitive system, including those people who say they are not.
I say this because every approach to AI involves something borrowed from
the human design: even pure mathematical logic was based on some ideas
that the Ancient Greeks had about how their minds worked. Most people
borrow just a little (nobody is trying, yet, to borrow most of the human
design).
2) The only reason that any AI design works is because something was
borrowed from the human design.
There are no objective reasons why AI systems should be intelligent, no
matter how much the logicians might argue that what they do is 'deriving
true facts about the world by means of truth-preserving laws of
inference'. This is just post-hoc rationalization that leaves out all the
little bits and pieces they insert into their systems to make them work in
practical situations. Those mathematical laws of inference do not
guarantee that the systems are intelligent, they just guarantee that if
you load up a system with a bunch of facts you can derive a bunch of
others.... these are two very different claims.
3) If you step back and ask, objectively, whether we should borrow a lot
of the human design, or just take a few snippets and then embellish them,
you can come to a serious conclusion, based on our understanding of
complex systems: the grab-a-few-snippets-and-then-embellish-them approach
is the most ridiculous of all. This approach is almost certain to fail
because if you want to emulate a complex system then the dumbest, most
lunatic approach of all is to take a quick glance at its low level
mechanisms and then pretend that your quick glance can be the root of a
development process that will lead to the same global behavior as the
original... basically, you are trapping yourself in a Can't Get There From
Here situation.
4) If the above problem (item 3) is real, then we would expect to see a
number of features in AI research:
(a) Avoidance of the crucial areas where the complexity will get you,
like true symbol grounding [CHECK],
(b) Encouraging progress at first because of the borrowing from the
human design, followed by stagnation [CHECK],
(c) Repeated cycles in which everyone climbs on a new idea-bandwagon to
try to get around the limitations of the previous one, followed by good
progress and then stagnation [CHECK],
(d) Very little to show for years of mind-numbing theorem-proving
[CHECK],
(e) Double standards by those who claim to be using rigorous scientific
(i.e. mathematical) techniques ... the core of what they do is rigorous,
to be sure, but they keep very quiet about the fact that they have to add
completely arbitrary machinery to 'constrain' their theorem proving
engines, so they won't just prove everything in the universe before
deciding whether to put the jam on top of the bread or the bread on top of
the jam. In other words, these people are just hackers, like their
predecessors. [CHECK],
(f) Distractions from the goal of building a working AGI, like people
who invent abstract, impossible-to-build AI 'systems' (actually just pure
math fantasies), because they love math more than they love the idea of
actually getting anything to work [CHECK],
(g) No overall progress, because this approach (borrowing a few ideas
from the human design, glorifying them as basic assumptions, and then
pretending that it is possible to make a complete AGI system by
embellishing and extending those first, arbitrarily chosen ideas) is
ultimately going to hit a glass ceiling. The approach will be able to
make some limited progress with all the aspects of intelligence that do
not depend on too much complexity (like getting the system to build its
own concepts and its own high-level learning mechanisms), but this will
only produce fragile systems that have to have their hands held in an
exponentially increasing way as we try to push them to do more intelligent
things.
That last point is the only one we don't know about yet: come back in
fifty years and see if, with no cahnge in approach, the situation is still
as daft as it is today.
Every one of the AI or AGI projects that I see now is doing the same
thing. All borrowing a few chunks from the human design, all pretending
that they don't need to borrow the entire human design, all just making it
up from a 'design' that is actually someone's best guess, with only
personal intuition as their ultimate justification for why their best
guess is the one that will work. All, I predict, will make some progress
until they hit the glass ceiling.
So what is the way out? The only way out, I claim, is to be honest about
the fact that the human design is the source of inspiration, and get
serious about borrowing from it in a massive, systematic way.
I am not saying that everyone should just do cognitive science: the folks
over there are just as screwed up as the AI community, though for slightly
different reasons.
What we actually need is a true middle path, neither conventional AI nor
cognitive science/psychology, but something in between. Absent a better
name, I am now referring to that middle course as 'Theoretical
Psychology'.
So the answer to your question is like this:
Nobody has a clue what a formal theory of AGI would look like, because in
the end there cannot be any such thing: the function "being intelligent"
is not definable in an objective, non-circular way. So I am afraid you
cannot ask for either experimental science or verifiable functional
components. Unfortunately, a lot of AI's problems are wrapped up in the
fact that people simply cannot get their heads around this idea. They
will one day, but why do we have to wait?
The best we can do is to use the human design as a close inspiration --
we do not have to make an exact copy, we just need to get close enough to
build something in the same family of systems, that's all -- and set up
progress criteria based on how well we explain and understand that design.
Sounds like it would be very unsatisfying to someone who was a
mathematican, doesn't it? Horrible, nasty, empirical science. That's
why, sadly, mathematicians should not be doing AI.
Richard Loosemore
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