_*Steps to a theory of reference & significance in information
*_*FIS discussion paper by Terrence W. Deacon (2015)*
This is the link to download the whole paper:
https://www.dropbox.com/s/v5o8pwx3ggmmmnb/FIS%20Deacon%20on%20information%20v2.pdf?dl=0
/"The mere fact that the same mathematical expression - Σ pi log pi
occurs both in statistical
mechanics and in information theory does not in itself establish any
connection between these
fields. This can be done only by finding new viewpoints from which
thermodynamic entropy and
information-theory entropy appear as the same concept." /(Jaynes 1957,
p. 621)
/"What I have tried to do is to turn information theory upside down to
make what the
engineers call 'redundancy' [coding syntax ] but I call 'pattern' into
the primary
phenomenon. . . . “/ (Gregory Bateson, letter to John Lilly on his
dolphin research, 10/05/1968)
*Introduction*
In common use and in its etymology the term ‘information’ has always
been associated with
concepts of reference and significance—that is to say it is about
something for some use. But
following the landmark paper by Claude Shannon in 1948 (and later
developments by Wiener,
Kolmogorov, and others) the technical use of the term became almost
entirely restricted to refer
to signal properties of a communication medium irrespective of reference
or use. In the
introduction to this seminal report, Shannon points out that although
communications often have
meaning, “These semantic aspects of communication are irrelevant to the
engineering problem”
which is to provide a precise engineering tool to assess the
computational and physical demands
of the transmission, storage, and encryption of communications in all forms.
The theory provided a way to precisely measure these properties as well
as to determine
limits on compression, encryption, and error correction. By a sort of
metonymic shorthand this
quantity (measured in bits) came to be considered synonymous with the
meaning of
‘information’ (both in the technical literature and in colloquial use in
the IT world) but at the cost
of inconsistency with its most distinctive defining attributes.
This definition was, however, consistent with a tacit metaphysical
principle assumed in the
contemporary natural sciences: the assertion that only material and
energetic properties can be
assigned causal power and that appeals to teleological explanations are
illegitimate. This
methodological framework recognizes that teleological explanations
merely assign a locus of
cause but fail to provide any mechanism, and so they effectively mark a
point where explanation
ceases. But this stance does not also entail a denial of the reality of
teleological forms of
causality nor does it require that they can be entirely reduced to
intrinsic material and energetic
properties.
Reference and significance are both implicitly teleological concepts in
the sense that they
require an interpretive context (i.e. a point of view) and are not
intrinsic to any specific physical
substrate (e.g. in the way that mass and charge are). By abstracting the
technical definition of
information away from these extrinsic properties Shannon provided a
concept of information that
could be used to measure a formal property that is inherent in all
physical phenomena: their
organization. Because of its minimalism, this conception of information
became a precise and
widely applicable analytic tool that has fueled advances in many fields,
from fundamental
physics to genetics to computation. But this strength has also has
undermined its usefulness in
fields distinguished by the need to explain the non-intrinsic properties
associated with
information. This has limited its value for organismal biology where
function is fundamental, for
the cognitive sciences where representation is a central issue, and for
the social sciences where
normative assessment seem unavoidable. So this technical redefinition of
information has been
both a virtue and a limitation.
The central goal of this essay is to demonstrate that the previously set
aside (and presumed
nonphysical) properties of reference and significance (i.e. normativity)
can be re-incorporated
into a rigorous formal analysis of information that is suitable for use
in both the physical (e.g.
quantum theory, cosmology, computation theory) and semiotic sciences
(e.g. biology, cognitive
science, economics). This analysis will build on Shannon’s formalization
of information, but will
extend it to explicitly model its link to the statistical and
thermodynamic properties of its
physical context and to the physical work of interpreting it. It is
argued that an accurate analysis
of the non-intrinsic attributes that distinguish information from mere
physical differences is not
only feasible, but necessary to account for its distinctive form of
causal efficacy.
Initial qualitative and conceptual steps toward this augmentation of
information theory have
been outlined in a number of recent works (Deacon 2007, 2008, 2010,
2012; Deacon &
Koutroufinis, 2012; Deacon , Bacigaluppi & Srivastava, 2014). In these
studies we hypothesize
that both a determination of reference and a measure of significance or
functional value can be
formulated in terms of how the extrinsic physical modification of an
information bearing
medium affects the dynamics of an interpreting system that exhibits
intrinsically end-directed
and self-preserving properties.
[...]
A model system
To test these principles and their relationship to reference and
significance, I and my
colleagues have conceived of an empirically realizable and testable
thought experiment. As in
most efforts to formalize basic physical properties it is useful to
begin with a simple model
system in which all aspects of the process can be unambiguously
represented. For our purposes
we describe a theoretical molecular system called an autogen, which
maintains itself against
degradation by reconstituting damaged components and reconstituting
system integrity. This
model system involves an empirically realizable molecular complex
described previously
(Deacon 2012; also in Deacon & Cashman 2012; and also called an autocell
in Deacon 2006a,
2007; 2009; and Deacon & Sherman 2008).
[...]
In this way we can use formal and simulated versions of autogenesis to
develop a measure of
relative significance, in the form of “work saved.” I hypothesize that
this simple model system
exemplifies the most basic dynamical system upon which a formal analysis
of informational
interpretation and significance can be based.
[...]
In both forms, modifications of the autogenic process is provided with
information referring
to its own preservation via boundary conditions (external or internal)
that are predictive of
successful self-preservation. The significance of information of either
sort is assessed by the
relative minimization of work per work cycle, and therefore the
decreased uncertainty of selfreferential
constraint preservation. In this way interpretation is analogous to the
decrease in
uncertainty that is a measure of received information in Shannonian
theory, but at a teleodynamic
system level.
Using these three variants of a simple model system I claim that we can
precisely analyze the
relationships between information medium properties, intrinsically
end-directed work, and the
way these enable system-extrinsic physical conditions to become
referential information
significant to system ends. These relationships are not only simple
enough to formalize, but they
can be simulated by computer algorithms at various levels of logical and
physical detail. I
believe that creating and experimenting with these simulated autogenic
systems will enable us to
reframe the mysteries of reference and significance as tractable
problems, susceptible to exact
formal and empirical analysis. This is still a far cry from a theory of
information that is
sufficiently developed to provide a basis for a scientific semiotic
theory much less than an
explanation of how human brains interpret information, but it may offer
a rigorous physical
foundation upon which these more complex theories can be developed.
*— Terry*
Professor Terrence W. Deacon
University of California, Berkeley
--
-------------------------------------------------
Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
Instituto Aragonés de Ciencias de la Salud
Centro de Investigación Biomédica de Aragón (CIBA)
Avda. San Juan Bosco, 13, planta X
50009 Zaragoza, Spain
Tfno. +34 976 71 3526 (& 6818)
pcmarijuan.i...@aragon.es
http://sites.google.com/site/pedrocmarijuan/
-------------------------------------------------
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