8 Computation --> Living
Systems
Most-recent shift:
Old language of computation: based in symbols, descriptive, reductive, pre-analyzed
New language of biology: based in action, interactive, integrating, dynamically-responsive
Dynamic error detection/correction and regulation are valid models of living
systems.
Limitations in metaphors of clockwork (Newton), machines (industrial age),
discrete computation (computer age)
Realization that organizations of all kinds are living systems
Informing from evolution and biology, not as metaphor but literally
Example of new language: "autopoiesis"
a "living system" means all its parts contribute to
the construction and maintenance of the whole (e.g. the components of a
living cell produce as well as keep alive that cell)
the processes internal to a living system also create and maintain the "boundary"
of that system (e.g. the cell produces and maintains its own cell membrane)
the system's boundary defines the system as distinct from the environment
(e.g. the cell's membrane maintains it as separate from other cells and
from its environment)
the system defines its own "identity" in the sense that the boundary's
properties define the system to the environment (e.g. the cell's identity
is mani-fest by its membrane's actions, which are defined by the internal
workings of the cell)
relationships among functional elements of a system (e.g. the
input of material, its use in internal transfor mations, the production
of by-products, the resulting energy made available)
are distinct from
how those relationships are actually reified (e.g. oxygen passes through
the membrane, is made available to mitochon dria, metabolism occurs through
the chemical reaction of oxygenation and transformation of specific enzymes)
variety in the environment must be countered (e.g. changing rates of metabolism
maintain internal steady-state)
when environmental variety cannot be handled with existing make-up, a new
identity is required - or, termination (e.g. evolution occurs from single-celled
to multi-celled organism)
Knowing (control) versus understanding (regulation, from detection and correction
of errors)
Knowing-before-acting as opposed to knowing-as-needed-in-interaction
Structural coupling: the history of recurring interactions among participants