The George Washington University
University Seminar on Reflexive Systems
Tuesday, April 12, 2011 from 10:00am - 12:00pm
Duques Hall, Room 652
2201 G Street NW
WHAT ARE THE RELATIONS BETWEEN ARTIFICIAL
AND BIOLOGICAL INFORMATION?
Jerry LR Chandler
Research Professor
Jerry_LR_Chandler@me.com
Krasnow Institute for Advanced Study, George Mason University
President, Washington Evolutionary Systems Society
Human communication of information is central to human being and human well-being.
The phenomenal successes of computers in recent decades amply attest to this hypothesis.
Advances in “Artificial Intelligence” have lead to popular sci-fi notions of eventual
“uploading” of our individual intelligence onto a computer. What is the relation between
our innate information processing capabilities and the engineering systems we have
constructed for artificial communication?
While the use of artificial informational signs and symbols vastly enrich our innate
biological capabilities, life itself is studied within the sciences of chemistry and genetics.
Our individuality emerges from the ancestors and our individual life experiences. Can the
codes of life itself be computed? Is induction alone sufficient to create the life of the mind?
A brief review of the history and philosophy of the various symbolic systems used in
human communication will be given to prepare for a discussion of the similarity and
differences between natural and artificial information. Semeiology (or semiotics) is the
science of the study of natural and artificial signs. The process of communication with
signs is called semeiosis. A new discipline, bio-semiotics has emerged in the past two
decades. It distinguishes artificial symbolic communication (semiotics) from natural
symbolic communication intrinsic to life (bio-semiotics.) This semantic distinction
separates the natural reflexivity of living and social systems from the artificial reflexivity
of physical and mechanical systems. For example, the hypothesis of G. Soros on the
operations of markets to illustrate natural reflexivity is clearly different from the artificial
reflexivity of modern mathematics such as in Shannon information theory.
How are we to understand the difference between semiotics and bio-semiotics? A short
review of historical origins of semiotics / bio-semiotics will start with the concept of
emergence of symbolic forms. Historically, the Sumerians, in the fourth millennium B.C.,
used signs impressed on clay tablets to record accounts of barley and beer. The ancient
scripts are interpreted without benefit of rhetoric or grammar; the association of sounds
with symbols is missing. The Greek alphabet emerged as symbols for both sounds and
numbers, effectively replacing both the cuneiforms and hieroglyphs symbols (consider the
scripts on the Rosetta stone.) Rhetoric, grammar, logic and calculus became expressible
within the Greek symbol system; this creates the opportunity for a rich synthesis of
reflexive interior relations. Greek philosophers exploited their individual reflexivity in
giving birth to Greek culture; the unique synthesis of Aristotle created a perspective of
mental life that remain germane today.
Using Aristotle's writings as a common but distant seed, Western philosophy developed
narratives of the interplay among conjectures, logic, values, calculations and the facts of
empirical science. Over the past three centuries, clearly distinguishable systems of
scientific thought have emerged. The distinctive reflexivity of mathematicians, physicists,
chemists, biologists, physicians, and other natural philosophers has generated numerous
symbol systems for explicit communication of natural concepts. The contributions of
Descartes (1596-1650), Newton (1642-1727), Kant (1724-1804), Hume (1711-1776),
Lavoisier (1743-1794) Dalton (1766-1844), Galois (1811-1832), Boole (1815-1864),
Mendeleev (1834-1907), Peirce (1839-1914) and more recently, Watson and Crick will be
integrated into a narrative describing the developments of scientific semiotics and
notations.
By the beginning of the 21 st Century, two intertwined semiotic conventions became the
"lingua franca" of basic scientific communication. Natural informational structures of life
(for example, anatomy, organs, cells, molecules) are composed from the basic elements of
matter, the chemical elements. Artificial electronic informational structures are composed
from continuous variables in terms of the International System of Units. In artificial
information, a generic concept of ‘mass’ replaces the concept of the individual identity of
matter.
The two semiotic systems encode sensory experience differently. The logic of natural
information encodes experience with a copulative grammar. The logic of artificial
information encodes experience with a predicative grammar.
The two semiotic conventions induce calculations differently. The encoding system for
chemistry, biology and medicine developed from ratios of small whole numbers in the
semiotic system of Lavoisier, Dalton, and Mendeleev. Scientists encode artificial
information in the semiotic system of continuous variables of Descartes and Newton by
translating artificial codes into Shannon “bits” of time or place. These two mathematical
systems use different notions of inductive logic. Can these two logical systems be brought
into congruence? In other words, can the relations of genetic systems be codified into bits
of artificial information? This question generates a strange historical paradox.
The polymath, C. S. Peirce, a chemist, while seeking a logic for chemistry, developed a
relational logic for mathematics. Peirce recognized that the relational logic of mathematics
excluded chemical logic! Today, we know that the natural logic of electrical structure of
atoms and molecules is a copulative, not a predicative, logic that conjoins parts into
wholes. The partition of relations into numerical parts generates the appropriate
mathematical base for natural information and the composition of living systems from
inert parts. (This special form of inductive logic was described in a paper, Introduction to
the Perplex Number System, 2008.)
Several philosophical differences distinguish natural information from artificial
information (when both are expressed as numbers). Some of the important conceptual and
formal differences are summarized in following table.
Concept
Natural Information
Artificial Information
Identity
Part-Whole Relation
Logical Relation
Number
Unit-Integer Relation
Distance Relation
Conjunction
Creates a new Identity
Creates a Class
Grammar (verb)
Copulative
Predicative
Formal Causality
Material
Efficient
Formal Mathematics
Labeled Bipartite Graphs
Topological spaces
Formal Inductive Logic
Synduction on Relations
“Peano” Induction
A common attribute of natural and artificial information is number - the logic of order. The
concept of order creates the basis for conjoining the meaning of the relational perplex
number system to a comparable meaning within the geometrically based number system.
The conjoining relations are termed the Rosetta relations and are well-known physicalchemical equations routinely used within the scientific communities to bridge the concept
space of chemistry to the concept space of physics. These mappings are not equivalence
relations.
(I am pleased to acknowledge multiple conversations on reflexivity with Lowell Christy
and Stuart Umpleby.)
McLean, VA
April 7, 2011