Knowledge representation for AI using domains or a universe of discourse

Dear all,

We have reached the point in time where we must start to generalize the
basis of knowledge representation for artificial intelligence.

In order to do so we must find (a) common denominator(s) for the different
types of knowledge.

Assuming that the knowledge is digitized we can use the concept of the
universe of discourse or more specifically domains of discourse.

These concepts lend themselves for use of set theory, type theory etc. and
allow modeling and constructibility of consistent logical frameworks.

And they also allow the use of (hyper)graphs, algebraic geometry, category
theory etc. to allow knowledge representation in ways that can be captured
for data (structure) creation, data analysis and machine learning.

In addition we can use classification systems to uniquely identify domains
of discourse as librarians do and as mathematicians do as well with the
Mathematics Subject Classification.

This can lead to a much more efficient use of datasets, the use of which
can be negotiated with the respective owners, avoiding the current
intellectual property and data rights, data and knowledge sovereignty
debates.

The indiscriminate use of scraping and unlimited production of internet
content by artificial intelligence is contaminating available data.

After having examined the current use of artificial intelligence for
solving sustainable development problems, both at global, regional and
local levels, the use of (open) curated and/or standardized datasets is the
only way to go.

This requires the use of a universe of discourse and more specifically
domains of discourse.


Milton Ponson
Rainbow Warriors Core Foundation
CIAMSD Institute-ICT4D Program
+2977459312
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean