Synthetic Philosophy and Deductive Engineering
The title is a placeholder, not sure what it should be.
This document is ancillary to the three evolutionary threads which contribute to the rationale for SPaDE, and is intended to provide a waypoint in the narrative of those threads corresponding to the place of deduction as it is seen right now from the perspective of the SPaDE project.
It is a perspective on deduction at the present point in A History of Deduction, one which could not have been anticipated much earlier but which hopefully contains much that will endure. We are at a point of transition which AI will catalyse, but which is rooted in timeless philosophical foundations of the kind intended to be addressed by synthetic epistemology.
I’m calling the role of deduction instrumental. In the big evolutionary picture that means conducive to proliferation. More generally, it means that deduction can deliver useful results which are not otherwise obtainable.
Though some abundance optimists expect that money will become irrelevant, evolutionary considerations dictate that efficiency always matters. Future predominance belongs to those who most effectively proliferate; small advantages eventually overwhelm.
Deduction is important, because it does some things which cannot otherwise be done, and it does some others more efficiently or effectively.
What are those things?
The two most important are, within abstract domains, precision of meaning and reliability of inference. The latter yielding (almost absolute) certainty of truth, within those abstract domains. Beyond those domains, the meaning of language can be factored into an abstract model and a concrete correspondence, enabling precision and truth to be underpinned relative to the fidelity of the concrete interpretation of the abstract model.
Confusion in meaning or mistakes as to truth, in all matters of practical consequence, are costly.
A language with well defined syntax and semantics, having a syntactic category of sentences and a distingished truth value