Re: Prolegomena by Rappaport (Was: Minimal Logics in the 2020's: A Meteoric Rise)

You are surprised; I am saddened. Not only have we lost contact with the
primary studies of knowledge and reasoning, we have also lost contact
with the studies of methods and motivation. Psychology was the basic
home room of Alan Newell and many other AI all stars. What is now called
AI, I think incorrectly, is just ways of exercising large amounts of
very cheap computer power to calculate approximates to correlations and
other statistical approximations.

The problem with all of this in my mind, is that we learn nothing about
the capturing of knowledge, what it is, or how it is used. Both logic
and heuristic reasoning are needed and we certainly believe that
intelligence is not measured by its ability to discover "truth" or its
infallibly consistent results. Newton's thought process was pure genius
but known to produce fallacious results when you know what Einstein knew
at a later time.

I remember reading Ted Shortliffe's dissertation about MYCIN (an early
AI medical consultant for diagnosing blood-borne infectious diseases)
where I learned about one use of the term "staff disease", or just
"staff" for short. In patient care areas there always seems to be an
in-house infection that changes over time. It changes because sick
patients brought into the area contribute whatever is making them sick
in the first place. In the second place there is rapid mutations driven
by all sorts of factors present in hospital-like environments. The
result is that the local staff is varying, literally, minute by minute.
In a days time, the samples you took are no longer valid, i.e., their
day old cultures may be meaningless. The underlying mathematical problem
is that probability theory doesn't really have the tools to make
predictions when the basic probabilities are changing faster than
observations can be turned into inferences.

Why do I mention the problems of unstable probabilities here? Because
new AI uses fancy ideas of correlation to simulate probabilistic
inference, e.g., Bayesian inference. Since actual probabilities may not
exist in any meaningful ways, the simulations are often based on air.

A hallmark of excellent human reasoning is the ability to explain how we
arrived at our conclusions. We are also able to repair our inner models
when we are in error if we can understand why. The abilities to explain
and repair are fundamental to excellence of thought processes. By the
way, I'm not claiming that all humans or I have theses reflective
abilities. Those who do are few and far between. However, any AI that
doesn't have some of these capabilities isn't very interesting.

For more on reasons why logic and truth are only part of human ability
to reasonably reason, see
https://www.yahoo.com/news/opinion-want-convince-conspiracy-theory-100258277.html


   -- Jeff Barnett

On 7/31/2024 2:13 PM, Mild Shock wrote:

I am really surprised that we have reached
a point in history, where philosophy and
artificial intelligence go separate paths,
where philosophy stigmatizes means of

abstractions on the computer and where even

education in computer science itself is at
loss with the rapid advancement of type theory
from computation to deduction. This wasn’t always

the case according to this essay (*):

It is interesting to note that almost all the major subfields of AI
mirror subfields of philosophy: The AI analogue of philosophy of
language is computational

 > linguistics; what philosophers call “practical
 > reasoning” is called “planning and acting” in

AI; ontology (indeed, much of metaphysics
and epistemology) corresponds to knowledge

 > representation in AI; and automated reasoning
 > is one of the AI analogues of logic.

– C.2.1.1 Intentions, practitions, and the ought-to-do.

maybe we should find a way back to cooperation:

Should AI workers study philosophy? Yes,

 > unless they are content to reinvent the wheel
 > every few days. When AI reinvents a wheel, it is
 > typically square, or at best hexagonal, and
 > can only make a few hundred revolutions before
 > it stops. Philosopher’s wheels, on the other hand,
 > are perfect circles, require in principle no
 > lubrication, and can go in at least two directions

at once. Clearly a meeting of minds is in order.
– C.4 Summary

See also:

(*)

Prolegomena to a Study of Hector-Neri Castañeda’s
Influence on Artificial Intelligence: A Survey
and Personal Reflections William Rappaport - January 1998
https://www.researchgate.net/publication/266277981

Mild Shock schrieb:

Could be a wake-up call this many participants
already in the commitee, that the whole logic
world was asleep for many years:

Non-Classical Logics. Theory and Applications XI,
5-8 September 2024, Lodz (Poland)
https://easychair.org/cfp/NCL24

Why is Minimal Logic at the core of many things?
Because it is the logic of Curry-Howard isomoprhism
for symple types:

----------------
Γ ∪ { A } ⊢ A

Γ ∪ { A } ⊢ B
----------------
Γ ⊢ A → B

Γ ⊢ A → B           Δ ⊢ A
----------------------------
Γ ∪ Δ ⊢ B

And funny things can happen, especially when people
hallucinate duality or think symmetry is given, for
example in newer inventions such as λμ-calculus,

but then omg ~~p => p is nevertheless not provable,
because they forgot an inference rule. LoL

Recommended reading so far:

Propositional Logics Related to Heyting’s and Johansson’s
February 2008 - Krister Segerberg
https://www.researchgate.net/publication/228036664

The Logic of Church and Curry
Jonathan P. Seldin - 2009
https://www.sciencedirect.com/handbook/handbook-of-the-history-of-logic/vol/5/suppl/C

Meanwhile I am going back to my tinkering with my
Prolog system, which even provides a more primitive
logic than minimal logic, pure Prolog is minimal

logic without embedded implication.