I think that the simple differentiation of programs as narrow AI or
AGI is overly simplistic. If there has never been an AGI program then
that would indicate that there probably never will be, or at least not
with contemporary computers.  Instead we need to be able to define
sub-programs as being Narrow AI or AGI.  For example, an AGI
subprogram might call Narrow AI functions (or subprograms).

Can we distinguish AGI subprograms from narrow AI and non-AI
subprograms?  I think that has to be done if you are going to attempt
to define AGI in a practical way.

I am going to refer to a subprogram as a function in this message even
though it might be a little confusing.

A function that does nothing other than output a value is not a Narrow
AI program.  A Narrow AI function has to produce outputs that are
dependent on learning and which can potentially be  used in further
learning. This means that a Narrow AI function must be closely related
to some other system of learning in the program.  Therefore, a
function that might be Narrow AI in one program might not be in
another program unless the resultants could be shared with a different
program that could use them in learning.

In order for a Narrow AI function to be used by an AGI function it
would have to be used in some way which would require and produce some
greater powers of judgement.  This means that the definition of an AGI
function, while dependent on a potential of further AGI actions,
cannot be defined simply by that dependence. So an AGI function has to
be produced by judgement-guided learning and it has to be potentially
useful in further judgement-guided learning.

I have a preliminary definition of artificial judgement so this
definition works for me.  However, many people have disagreed with my
definition.  I define judgement as a process of decision or
contemplation which is dependent on many learned processes.  This
definition is not quite strong enough because a simplistic logical
decision process could be qualified as judgement.  I came up with the
Conceptual Typing theory to distinguish between simple logical or
other simple mathematical functions and AGI learning.  So a
requirement of AGI judgement is that a potential variety of kinds of
Conceptual Types have to be used to make a decision.  To give you a
simple example a causative relation is not defined by logic alone.
(You could define a logical process by reference to a relation of
causation but you need that reference and a potential to discover
other relations dependent on it.)  A Conceptual Typing not only allows
for a programmer defined typing of a Concept but it also allows for
the dynamic definition of a Concept Type as well.  So judgement has to
be dependent on the application of Conceptual Types.  This is not
quite strong enough but it is a start.

I hope this helps someone, other than just me. -Jim Bromer


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AGI
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