Saturday, June 24, 2006
Generative Methodology Glass Bead Games
Transactions in the social discourse
The metaphor between gene, cell and social
expression à [217]
On Formal verses Natural systems à [206]
Link to education commons à [***]
I have often felt that there is a structure to how time expresses. By this, I have meant that human
communicative acts are motivated by a horizon whose features are interpreted by
individuals according to the individual constituent motivations and
capabilities. This constituent-based
interpretant has also cultural expressions that the individual is at least
partially embedded within.
The cultural expression has from one moment to the next, and in a
complex non-linear way, a self-replicating feature. There is cultural identity, and this cultural identity could be
described in human language, with a specific taxonomy of terms and phrases,
with semiotic (sign) systems, or even with a structured information space such
as a web ontology language or topic map based information space.
The individual identity has also a self-replicating feature, following mechanisms
that biologists see in gene and cell replication functions. As Nobel Prize winner in immunology, Gerald
Edelman, discusses in “Neural Darwinism”; this self replicating mechanism has a
response, many to many, degeneracy that allows a delay in the distribution of
energy in metabolic reaction pathways and thus facilities the making of choices
based on the availability of substrate materials in real time in the real
world.
The production of a sign system that properly represents the individual
is problematic for two reasons.
First, the natures of individuals are each quite different one
individual to the next. The cultural
identity does to some extent truncate these differences in much the same
fashion as individual words or phrases elicit a standardizing semantics. The elicitation is formative and constrains
meaning or opens up possible meaning.
Web ontology language (the W3C’s OWL standard) constrains meaning and
then pretends that the “inference” possible with well-formed OWL constructions
is “open” to meaning that is responsive to real world measurement in real
time. This is the dangerous illusion
that OWL creates.
Human awareness, unlike, OWL constructions, will not only constrain the
meaning of archetypical and categorical symbols, but also often increases the
uncertainly of an interpretation when circumstances appear to require. This increase in semantical uncertainty
opens the individual’s cognitive and response mechanisms to an investigation. The investigation involves being “open” to
the real world in real time. Action
perception cycles follow, such as occurs in normal sight.
The “OWL inference” truncates the investigation to what is hard wired
into the OWL construction by the class – subclass assertions and the inference
rules standardized by the W3C technical specification.
The meaning of things said is interpreted within the context of the
cultural identity and a social setting.
I like to use the term “reify” to mean the collapse of intrinsic meaning
into something truncated to fit within some set of stable categories. So, in my work on commodity transactions for
US Customs, or in work on taxonomy for context management; we say that the
semantics of the terms or phrases are reified when standards are created for
expressing these categories.
This reification of the semantics of taxonomy or web-ontology follows
only partially the collapse of the “meaning of“ real things into interpreted
category. We see this at all levels of
physical reality, as in the collapse of the non-localized quantum wave into a
localized particle.
The profession of artificial intelligence has in the past made this
categorical collapse dependant on pre-existing structure, defined in some way
without a true measurement of the real world in real time. The reification is castrated, not able to
make a connection to the natural self-replicating mechanisms as they exist and
operate in the pragmatics of the real world in real time.
The dangerous mistake is to place the phenomenon of artificial intelligence
into the same category as natural intelligence. The mechanisms are quite different, and the outcomes of processes
defined by these two kinds of things are quite different in some cases.
These cases, where the differences are significant, are those where the
stable interpretant categories are not sufficient in automatically categorizing
the natures and meanings of state transitions occurring in the natural world in
real time.