The relationship between physical and informational reductionism is a telling one, for it directly mirrors Cartesian mind-matter dualism, the source of several centuries of philosophical and scientific controversy regarding the nature of deep reality.  As long as matter and information remain separate, with specialists treating one as primary while tacitly relegating the other to secondary status, dualism remains in effect.  To this extent, history is merely repeating itself; where mind and matter once vied with each other for primary status, concrete matter now vies with abstract information abstractly representing matter and its extended relationships.  But while the formal abstractness and concrete descriptiveness of information seem to make it a worthy compromise between mind and matter, Berlinski’s comment demonstrates its inadequacy as a conceptual substitute.  What is now required is thus what has been required all along: a conceptual framework in which the relationship between mind and matter, cognition and information, is made explicit.  This framework must not only permit the completion of the gradual ongoing dissolution of the Cartesian mind-matter divider, but the construction of a footworthy logical bridge across the resulting explanatory gap.

Mathematically, the theoretical framework of Intelligent Design consists of certain definitive principles governing the application of complexity and probability to the analysis of two key attributes of evolutionary phenomena, irreducible complexity and specified complexity.  On one hand, because the mathematics of probability must be causally interpreted to be scientifically meaningful, and because probabilities are therefore expressly relativized to specific causal scenarios, it is difficult to assign definite probabilities to evolutionary states in any model not supporting the detailed reconstruction and analysis of specific causal pathways.  On the other hand, positing the “absolute improbability” of an evolutionary state ultimately entails the specification of an absolute (intrinsic global) model with respect to which absolute probabilistic deviations can be determined.  A little reflection suffices to inform us of some of its properties: it must be rationally derivable from a priori principles and essentially tautological in nature, it must on some level identify matter and information, and it must eliminate the explanatory gap between the mental and physical aspects of reality.  Furthermore, in keeping with the name of that to be modeled, it must meaningfully incorporate the intelligence and design concepts, describing the universe as an intelligently self-designed, self-organizing system.

How is this to be done?  In a word, with language.  This does not mean merely that language should be used as a tool to analyze reality, for this has already been done countless times with varying degrees of success.  Nor does it mean that reality should be regarded as a machine language running in some kind of vast computer.  It means using language as a mathematical paradigm unto itself.  Of all mathematical structures, language is the most general, powerful and necessary.  Not only is every formal or working theory of science and mathematics by definition a language, but science and mathematics in whole and in sum are languages.  Everything that can be described or conceived, including every structure or process or law, is isomorphic to a description or definition and therefore qualifies as a language, and every sentient creature constantly affirms the linguistic structure of nature by exploiting syntactic isomorphism to perceive, conceptualize and refer to it.  Even cognition and perception are languages based on what Kant might have called “phenomenal syntax”.  With logic and mathematics counted among its most fundamental syntactic ingredients, language defines the very structure of information.  This is more than an empirical truth; it is a rational and scientific necessity.