Kineman, J. 1997. Theory of Autevolution

Discussion II:

The principle of uncertainty in autevolution

Form-function complimentarity
Teleology
Non-deterministic behavior
Observer participancy and biological phenomena
Biological optimization
Selective feedback
Coevolutionary implications
Resemblance to information theory

Form-function complimentarity

The autevolution view would be forced by the preceding arguments
to treat purpose as a real quantity that is determined at the
organismic level; and perhaps modeled best as the amplification
of observership, which thus provides the theoretical basis for
creativity at the organismic level. The presence of sophisticated
biological examples for the magnification of this phenomena (observership),
as noted earlier, implies that self-determination has evolved
from rudimentary beginnings at the most fundamental level of material
existence. Innovation at the organismic level may then exhibit
original effects on the environment and, therefore, selection.
This implies a complementarity
between form and function over the course of generations,
where (as in quantum physics) observation of one aspect results
in change in the other, and both cannot be simultaneously defined.
It would thus be impossible for living organisms to exactly determine
both form and function, because functional definitions must allow
morphological uncertainty and vice versa. This property of indeterminacy
between form and function, from its simplest beginnings, must
be assumed to exist in anything we call life. In contrast to the
mechanistic view that function is determined solely by the relationship
between morphology (including behavioral programs) and the environment
(thus allowing for no inputs from the present), autevolution would
formally assume that function, though largely influenced by genetics,
development, and environment, is self-defined or modified (i.e.,
independently of prior selective factors and present environmental
controls). This self-definition could then lead to future evolutionary
forms that are not strict derivatives of independent environmental
selection, but may in fact have and be partly the result of creative
influences on their environment. This does not imply that we can
study the source of self-definition, just as the Heisenberg uncertainty
principle does not imply a study of uncertainty itself, but rather
formulates theory around the limits to uncertainty. As argued
earlier, an interdisciplinary autevolution theory requires formalization
in much the same way, from these founding assumptions.

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Teleology

An important issue is whether the question of teleology can be
resolved by identifying the source of novelty as observer-participancy.
Certainly any biological purpose of exclusively external origin
violates the ability to form testable causal hypotheses in the
same way that theistic views do, as there can be no process by
which external purpose (final cause) can drive behavior, development,
or evolution, unless it is reflected as an internal drive. The
question considered here is if the appearance of purposeful goals
can be treated scientifically if they are of internal definition
within the system (or organism) under study.

Of course, as a general principle that can apply equally to the
simplest and most complex of organisms, the concept of purpose
must not be equated with consciously and knowingly planning for
future events, as in the human case, which is clearly a recent
evolutionary complexity (Crook, 1980;
Wilbur, 1986). Still,
the ability, expressed according to the complexity of the organism,
to define function, expressed through novel behavior, would be
an unrecognized case in Mayr’s definitions, falling short of cosmic
teleology but going beyond teleonomy (programmed direction where
the program is strictly a result of prior selection). The case
would rather be that functional definitions can alter teleonomic
programs and provide them with an implied goal. To the extent
that a future state can be represented by present function, this
comes perhaps uncomfortably close to the notion that an end state
can be causally effective.

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Non-deterministic behavior

It is thus critical to this and similar worldviews to formally
de-couple behavior from genetic determinism by providing an alternative
causal process, yet this point is missed in recent accounts. Augros and Stanciu (1988),
in a popular account, for example, miss this point entirely by
arguing that the “new biology” cannot be derived from
physical principles; whereas, presumably, the point is that it
cannot be derived from classical (deterministic) principles. Even
Plotkin’s (1988) account
does not provide a causal basis for “novelties” expressed
as behavior. There are, meanwhile, a number of deterministic theories
that relate function (and behavior) solely to genetics or other
physical determinants, as in mechanical response to stimuli. It
is by no means accepted among biologists that even human psychological
experiences such as “free-will” are other than deterministic
or genetic manifestations. Honderich (1988),
for example, attempts to defend a deterministic approach for explaining
even psychological phenomena associated with life (e.g., free-will,
life hopes, etc.), but side-steps the obvious problem of quantum
theory by claiming that it will one day be replaced by determinism
(apparently ignoring evidence to the contrary). Such claims can
be used to defend anything, and thus are useless — we must work
with the evidence at hand.

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Observer participancy and biological phenomena

Although everyone is in doubt about the full implications of observer
participancy, the principle is being linked to biological phenomena.
A formal treatment of the relationship between observership and
perception (“observer mechanics”), for example,
has been published (Bennett et al., 1989).
Since there would be little reason to doubt a connection between
perception and behavior, a causal chain may be possible. Incorporating
observership into models of how organisms translate form into
function (and vice-versa) introduces a process that may also help
explain evolutionary novelty at the system level. As a possible
scenario, behavioral innovations may create a positive selective
feedback, through the effect of environmental modification on
the development and behavior of future generations, including
other species. As natural selection is assumed to favor characteristics
that are adaptive to the new environment, behavioral and functional
innovations in one species could, in this way, influence the selection
of even unrelated organisms, and thus become “registered”
in the course of evolution.

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Biological optimization

This view poses problems for optimization theories, stating that
optimization would be impossible beyond a specific limit set
by the fundamental uncertainties in the system (which, as
yet, we have no way to quantify). This uncertainty principle also
implies that we could not assume that a theoretical “optimal”
actually exists, as a given state would be the combined effect
of adaptation and unpredictable functional definitions that ensure
nonequilibrium.

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Selective feedback

Under such a view, even a slight ability to alter function
could stimulate selective feedback and become self-reinforcing,
giving rise to seemingly purposeful trends that actually reflect
functional decisions made at the individual level. This means
that we would have to view the course of evolution as partially
determined by the organism, although not in the Lamarckian sense,
but over the course of many generations through the combined effect
of behavioral choices, their effect on the environment, and reciprocal
selection. In a very real sense, selective forces would be seen
as partly co-created by the organism; increasingly so in accordance
with organismic complexity (e.g., Corning, 1983).
It could also be suggested that the ability to affect evolution
in this way has itself been selected for; thus creating a teleomatic
process in evolution that may partly explain the emergence of
the extreme capabilities of humans in this regard, with the further
complexification of self-awareness, or consciousness (Crook, 1980,
Wilber, 1986).

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Coevolutionary implications

The possibility for natural selection to reward (and register)
innovative behavioral interactions and environmental modifications
would likely have coevolutionary implications in terms of interactive
complexities (Corning, 1983;
Goldberg, 1989). In
a highly simplified example, Axelrod (1984)
proposed a model of strategic interactions in terms of game theory
(the prisoner’s dilemma) to explain the evolution of cooperation.
In this model, cooperative strategies emerge naturally from rudimentary
organismic abilities, which are all included within the view considered
here. These abilities are: (1) motivation for gain (self-defined
purpose); (2) ability to recognize the presence or absence of
benefits ( perception and self-reference); and (3) ability to
modify behavior in innovative ways, based on current experience
(observership or decision making). Given these basic psychobiological
abilities (which in actual life would operate entirely in the
present, not presupposing conscious awareness, memory, or intellectual
reasoning; and given an environmental context that favors long-term
interactions; the emergence of coevolutionary and cooperative
systems is predicted at many levels of complexity.

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Resemblance to information theory

Similarly, autevolution, as described, may bear a close resemblance
to information theory, since by accepting organismic life as a
causative agent (i.e., source of novelty), information and self-determination
can become driving forces for system phenomena. Current theory
relates life form with information by identifying DNA as the primary
agent for defining organismic structure. But the evolutionary
complementarity between form and function proposed here suggests
a continuous interchange of information between organism and environment
over generations, where decisions partly determine function,
which may then modify and direct the evolution of form. It is
interesting to speculate that, given this process, the basic model
presented in Figure 1 for the growth
of intellectual knowledge may also be a model for the evolution
of species, complex organisms, communities, and ecosystems.