Jim, 

 

I see prediction as essential for survival. In order to survive we need to
predict the consequences of what we do to the world. We predict by
establishing chains of causality, hence the importance of causality in
survival.

 

You are discussing a different angle. You are discussing the use of
prediction for verification of theories. But isn't that also a form of
prediction? You predict something, then compare your prediction with what
actually happened in the world, and adjust your process of prediction in
order to account for what really happened. 

 

Would you explain your take on this?

 

Sergio

 

 

From: Jim Bromer [mailto:[email protected]] 
Sent: Tuesday, June 19, 2012 2:19 PM
To: AGI
Subject: Re: [agi] Prediction Did Not Work (except in narrow ai.)

 

Piaget Modeler (I can't remember your real name),

 

This is my insight into the absurdity of using "prediction" as a key AGI
concept of verification.  Just like all the other narrow tools, it works
well for some situations (that are rightly or wrongly called "narrow" in
this group) while failing completely in other situations.  The problem is
that confirmation through prediction has to be predicated on absolute
knowledge (about the correctness of something predicted) in which case it
makes the methods contradictory when used for uncertainty or any conditions
that uncertainty can be found.

 

In the early years of AI it was believed that the method might be used to
confirm theories that a strong AI program might create.  However, since
confirmation is based on absolute knowledge it really was only an illusion
even from the beginning.  In other words confirmation (or disconfirmation)
through prediction is not a solution for uncertain knowledge because, like
logic, it relies on certainty.

 

I am really amazed that you guys do not seem to get this.  Of course you can
use expectation (calling it anything you want) and probability along with
evidentiary methods because when you lack certainty then anything goes no
matter what you try and the best you can do is muddle through.  There is
nothing to replace lost certainty so you are going to end up using uncertain
methods anyway.

 

Of course we adults feel that we are certain about a great many things and
our reasoning is largely based on these things or at least related to these
things.  And if AI or AGI were able to achieve some basic level of human
knowing like that which we take for granted then these methods probably
would be satisfactory.  A great many principles from the philosophy and
science of mind could probably be used to power an AI or AGI program if
contemporary AGI was at a basic human level. However, AGI programs (and
almost all AI programs) are so primitive or narrow, that the presumption
that a principle of "prediction" could be combined with probability to
achieve certain knowledge is absurd.  I agree that Watson's game of Jeopardy
is not just "narrow AI" but it is based on "certain knowledge" that can be
construed by the appearance of a "fact" in one of a few sources.  What makes
Watson so amazing that it relies (seems to rely on) some combination of  NLP
along with some kind of highly automated NL notation of text.

 

Jim Bromer

On Tue, Jun 19, 2012 at 1:48 PM, Piaget Modeler <[email protected]>
wrote:

Jim, 

 

Is this your actual belief or is this disinformation? 

  _____  

Date: Tue, 19 Jun 2012 10:40:22 -0400
Subject: [agi] Prediction Did Not Work (except in narrow ai.)
From: [email protected]
To: [email protected]

 

The original idea behind the use of "prediction" in AI was that the
prediction could be compared against the actuality and that comparison could
be used to test the theory that produced the prediction.  (Some author
popularized that model for AI but it was proposed by academic researchers
before he did so. Karl Popper used the concept as part of his model of
scientific discovery in the 1930s, but his principles, which were based on
logical positivism, have become more dubious because logical certainty has
become a more dubious principle of knowledge. And, oh, by the way, Popper
did not believe that AI was possible.)  So, continuing with the march of the
use of "prediction" in AI, AI people could see that our expectations were
like "predictions" and so it did seem that the human mind did indeed use a
method of prediction.  Of course the principle that a prediction could be
compared against an actuality in order to evaluate the accuracy of a theory
only works in narrow AI, and as narrow AI failed to produce simple AGI that
part of the cherished notion of "prediction" has been gradually eroded.

 

This group uses the term prediction to simply refer to something that is
"known" and as such it is a concept which is pretty shallow since its
verification as a mental product is thereby based on the experience that
when we know something we act as if we were confident that it would happen.
The problem with such concepts like "knowing" or "prediction" is that they
-do not- confirm the efficacy of theories that an AGI program might produce,
except in those circumstances which would be considered narrow AI by this
group.

 

Let me repeat that.

The problem with such concepts like "knowing" or "prediction" is that they
-DO NOT- confirm the effaciacy of theories that an AGI program might
produce, except in those circumstances which would be considered narrow AI
by this group.

 

So sure, when someone points out that the human mind uses "expectation" and
expectation is a little like "prediction" I do agree.  But here the word
prediction is just being used to describe "knowing something."  There is no
principle of confirmation or disconfirmation of the use of "prediction" that
can be used to produce AGI, except for special cases.  After years and years
of the repetition of the word in these types of discussions there is still
no AGI so that should give you a hint about how good an idea it was. 

 

If the use of prediction as a confirming method can only be used in a
limited set of circumstances then its power in these discussions has been so
diminished that it should not be used as if it were a magical concept.
Without some efficacy the word should not be used as a special technical
term.  The word should be used in the way it is usually used.

 

As I implied, Popper originally used the word the concept in a logical model
of scientific theory.  If a theory could be used to predict a confirming or
disconfirming observable event then the theory could be disconfirmed by the
failure of the event to occur.  (If the event occurred it still might be
caused by a coincidence.)

 

It is coming back to me. (Or else my creative memory is kicking in.)  The
author who popularized the theory of confirmation through prediction had a
model of probability and confirmation by prediction.  That model is
inherently contradictory. 

 

It amazes me that you guys don't get this.

 

Jim Bromer


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