This post is a summation of a few ideas posted by Pat Hayes as part of an exchange that can be found in much greater detail on the W3C Semantic Web list group: https://lists.w3.org/Archives/Public/semantic-web/2019Jun/0157.html
These thoughts were in response to a previous e-mail in the thread – but I think they express some very succinct ideas that could be separated out and perhaps expanded upon by Pat in this post:
Most (all?) of the KR (Knowledge Representation) proposals put forward in AI or cognitive science work have been some subset of first-order predicate logic, using a variety of surface notations. There are some fairly deep results which suggest that any computably effective KR notation will not be /more/ expressive than FO logic. So FOL seems like a good ‘reference’ benchmark for KR expressivity.
Avoiding KR silos was one of the primary goals of the entire semantic-web linked-data initiative. But this has many aspects. First, we need to agree to all use a common basic notation. Triples (=RDF =Knowledge Graph =JSON-LD) has emerged as the popular choice. Getting just this much agreement has taken 15 years and thousands of man-hours of strenuous effort and bitterly contested compromises, so let us not try to undo any of that, no matter what the imperfections are of the final choice. The next stage, which we are just getting started on, involves agreeing on a common vocabulary for referring to things, or perhaps a universal mechanism for clearly indicating that your name for something means the same as my name for that same thing. This seems to be much harder than the semantic KR pioneers anticipated. The third stage involves having a global agreement on the ontological foundations of our descriptions, what used to be called the ‘upper level ontology’. This is where we get into actual metaphysical disagreements about the nature of reality (are physical objects extended in time? How do we handle vague boundaries? What are the relationships between written tokens, images, symbols, conventions and the things they represent? What is a ‘background’? What is a ‘shape’? Is a bronze statue the same kind of thing as a piece of bronze? What changes when someone signs a contract? Etc. etc., etc.) This is where AI-KR and more recently, applied ontology engineering (not to mention philosophy) has been working for the past 40 or 50 years, and I see very little hope of any clear agreements acceptable to a large percentage of the world’s users.