Camilo Olaya
An evolutionary stance is interested in explaining change which is assumed as a principle of nature and living systems, including social systems. Invariances and regularities are rejected as starting points.
How does evolution proceed? It can be characterized as the continuous sequence of two steps: (i) Variations that provide material upon which selections acts on. (ii) Selection due to the elimination of unsuccessful forms by the environment or by internal constraints or internal selection processes. Since the very idea of process implies trans-temporal constancies we can safely say that every particular process is an instantiation of a general, atemporal and generic pattern (Rescher, 2008). The variation + selection combination forms an algorithm with substrate neutrality, that is, its logical structure implies guaranteed results independent of the “materials” that happen to be used to carrying it out (Dennett, 1995). This abstractness provides a generic schema that can be instantiated to give an actual theory (Darden & Cain, 1989) by proper theoretical recontextualization in specific domains (Dopfer, 2005; Hayek, 1942). Selection theory is perhaps the most accepted explanation of generic processes of fit, that is, the explanation of satisfaction relationships in which one thing comes to be adapted to another thing (Bickhard & Campbell, 2003; Cziko, 1995; Darden & Cain, 1989). This statement asserts then that selection defines an abstract form of explanation in which the process itself is the explanans.
I prefer to choose the terms selectionist thought over the more
general expression evolutionary
thought. "Selection" places the emphasis on the opposition to
"instruction"; the latter one has been widely used in evolutionary
thought in fields outside biology; such a view holds what can be
labelled as "Lamarckian" assumptions regarding evolutionary processes
which I find inconvenient not only in biology but in general in any
evolutionary conception.
Instruction
Selection
Evolution
of knowledge
Social systems can be understood as a
special type of systems defined by knowledge evolutionary regimes
driven by the social agents that conform the system. I endorse the
definition of Campbell (1987):
Knowledge
refers to any process providing a stored program for organismic
adaptation in external environments. Moreover, any gain in the adequacy
of such a program is regarded as a gain in knowledge. Therefore,
evolution is conceived as a process in which information regarding the
environment is literally incorporated in organisms; adaptation is an
increment of knowledge which is driven by the logic of selection.
Two major steps can be indentified
behind this creative force.
(i)
Variation : The process of variation provides the ”raw
material”; this variation should be generated in copious and dependable
amounts and should be undirected. For knowledge processes Campbell
coined the expression blind variation
(which does not mean "random"); the term ”blind” denotes the fact that
variations are produced without prior knowledge of which ones, if any,
will furnish a selectworthy encounter. Three connotations are
paramount: (i) The variations emitted are independent of the
environmental conditions of the occasion of their occurrence. (ii) The
individual occurrences of trials are uncorrelated with the solution —
specific correct trials are no more likely to occur at any point in a
series of trials than another correct one, nor than specific incorrect
trials. (iii) The rejection of the notion of a "correcting" process
between variations, that is, a variation subsequent to an incorrect
trial is not a "correction" of an earlier one.
(ii)
Selection : The direction of evolutionary change is granted to
the second step, selection as such, which works upon variation.
Selection occurs due to the elimination of unsuccessful forms by the
environment and through a hierarchy of flexible controls (as suggested
by Popper and Campbell). The general logic of problem solving is trial
and error-elimination through this hierarchical system of flexible
controls. For instance Campbell remarked that general knowledge
processes involve several mechanisms at different hierarchical levels
of substitute functioning; at each level — a type of template — there
is a form of selective retention process; regarding human knowledge, he
identified several levels ranging from the most primitive non-mnemonic
problem solving layer, through higher levels like habit, instinct,
visually and mnemonically supported thought, imitation, to the highest
levels such as language, cultural cumulation, and science. Evolving
selection criteria are nested in this hierarchy; what are criteria at
one level are but `trials' of the criteria of the next higher level. It
must be emphasized that within those layers, a trial and
error-elimination logic takes places as well.
Thus, variations and selections of
knowledge can form a base for studying and designing social systems. A
detailed argument can be found in my
doctoral thesis.
References
Bickhard, M. H., & Campbell,
D. T. (2003).
Variations In Variation And Selection:The Ubiquity Of The
Variation-And-Selective-Retention Ratchet In Emergent Organizational
Complexity. Foundations of Science, 8,
215-282.
Campbell, D. T. (1987).
Evolutionary Epistemology. In G. Radnitzky & W.W. Bartley, III
(Eds.), Evolutionary Epistemology, Rationality, and the Sociology of
Knowledge (pp. 47-89). La Salle, IL, USA: Open Court.
Cziko, G. (1995). Without
Miracles. Universal Selection Theory and the Second Darwinian
Revolution. Cambridge, MA, USA: MIT Press (A Bradford Book).
Darden, L., & Cain, J.
A. (1989). Selection Type Theories. Philosophy of Science, 56,
106-129.
Dennett, D. C. (1995).
Darwin's Dangerous Idea. The Sciences (May/June), 34-40.
Dopfer, K. (2005). The
Evolutionary Foundations of Economics Cambridge, UK: Cambridge
University Press.
Hayek, F. A. v. (1942). Scientism
and the study of
society (Part I). Economica, New Series,
9(35), 267-291.
Rescher, N. (2008). Process Philosophy. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. Stanford, CA: The Metaphysics Research Lab, Stanford University.