On 12/1/2010 4:58 PM, Jim Devine wrote:
Jay Hanson wrote:
Evolutionary psychology is quickly becoming the ONLY psychology.
Man, is that arrogant! Remember that 100 years ago or so, Freudianism
quickly became the ONLY psychology. Then, behaviorism quickly became
Only time will tell Jim. The difference is that EP is not a social
science, it a true science. /EP can even explain why social scientists
are so afraid of it. <G>/
I encourage all of you all on this list to read it.
Jay
==============
*^THE HANDBOOK OF EVOLUTIONARY PSYCHOLOGY, *^Buss Ed., 2005,
pp. 12-14. Chapter 1, The Conceptual Foundations of Evolutionary
Psychology, John Toby and Leda Cosmides
Many members of the evolutionary research communities believed that the
new selectionist theories straightforwardly applied to humans, although
others continued to welcome the Standard Social Science Model arguments
that learning had insulated human life from evolutionary patterning.
Human behavior exhibited many patterns that offered ready selectionist
interpretations (e.g., sex differences in the psychology of mating), but
many other phenomena resisted easy interpretation and seemed to lack
clear nonhuman analogues (e.g.,morality, the arts, language, culture).
The result was a rich and contradictory pluralism of ideas about how
evolution relates to human affairs---a pluralism that is still with us.
One of the most widespread approaches to emerge is what might be called
fitness teleology. Teleological explanations are found in Aristotle, and
arguably constitute an evolved mode of interpretation built into the
human mind. Humans find explaining things in terms of the ends they lead
to intuitive and often sufficient (Baron-Cohen, 1995; Dennett, 1987;
Leslie, 1987, 1994). Social science theories have regularly depended on
explicitly or implicitly teleological thinking. Economics, for example,
explains choice behavior not in terms of its antecedent physical or
computational causes but in terms of how the behavior serves utility
maximization. Of course, the scientific revolution originated in
Renaissance mechanics, and seeks ultimately to explain everything
(non-quantum mechanical) using forward physical causality---a very
different explanatory system in which teleology is not admissible.
Darwin outlined a physical process---natural selection---that produces
biological outcomes that had once been attributed to natural
teleological processes (Darwin, 1859). Williams (1966) mounted a
systematic critique of the myriad ways teleology had nonetheless
implicitly infected evolutionary biology (where it persists in Darwinian
disguises). Computationalism assimilated the other notable class of
apparently teleological behavior in the universe---the seeming goal
directedness of living systems---to physical causation by showing how
informational structures in a regulatory system can operate in a forward
causal way (Weiner, 1948). The teleological end that seems to exist in
the future as the point toward which things tend is in reality a
regulatory process or representation in the organism in the present. The
modern scientific claim would be that adaptationism and computationalism
in combination can explain by forward physical causation all events that
once would have been explained teleologically.
Yet, the implicit or explicit substrate underlying many attempts to
apply Darwinism to human behavior was a return to the sense that human
behavior was explained by the ends it serves. For a Darwinian, it was
argued, choices, practices, culture, and institutions were explained to
the extent that they could be interpreted as contributing to individual
(or sometimes group) reproduction: That is, the explanation for human
behavior is that it naturally tends toward the end of maximizing
reproduction in the present and future. This theory---Darwinism
transmuted into fitness teleology---parallels the economic view of
individuals as selfish utility maximizers, except that Hamilton's (1964)
concept of inclusive fitness is substituted for the economists' concept
of utility. Both approaches assume that unbounded rationality is
possible and that the mind is a general-purpose computer that can figure
out, in any situation, what will maximize a given quantity over the long
term (whether utility or children). Indeed, the concept of "learning"
within the Standard Social Science Model itself tacitly invokes
unbounded rationality, in that learning is the tendency of the
general-purpose, equipotential mind to grow---by an unspecified and
undiscovered computational means---whatever functional
information-processing abilities it needs to serve its purposes, given
time and experience in the task environment.
Evolutionary psychologists depart from fitness teleologists, traditional
economists (but not neuroeconomists), and blank-slate learning theorists
by arguing that neither human engineers nor evolution can build a
computational device that exhibits these forms of unbounded rationality,
because such architectures are impossible, even in principle (for
arguments, see Cosmides & Tooby, 1987; Symons 1989, 1992; Tooby &
Cosmides, 1990a, 1992). In any case, observed human behavior
dramatically and systematically departs from the sociobiological
predictions of generalized fitness striving (as well as the predictions
of economic rationality and blank-slate learning abilities). To take one
simple contrast, men will pay to have non reproductive sex with
prostitutes they believe and hope are contracepting, yet they have to be
paid to contribute to sperm banks. More generally, across a range of
wealthy nations, those able to afford more children choose to have fewer
children---a striking disconfirmation of the prediction that humans
teleologically seek to maximize reproduction or fitness (Vining, 1986).
Human life is permeated with systematic deviations away from rationally
maximized child-production and kin assistance.
For those eager to leap directly from theories of selection pressures to
predictions of fitness maximization, there remains a missing level of
causation and explanation: the informational or computational level.
This level cannot be avoided if the application of Darwin's theory to
humans is ever to achieve the necessary level of scientific precision.
Natural selection does not operate on behavior per se; it operates on a
systematically caused relationship between information and behavior.
Running---a behavior---is neither good nor bad. Running away from a lion
can promote survival and reproduction; running toward a lion will
curtail both. To be adaptive, behavioral regulation needs to be
functionally contingent on information; for example, flee when you see a
stalking lion. But a systematic relationship between information and a
behavioral response cannot occur unless some reliably developing piece
of organic machinery causes it. These causal relations between
information and behavior are created by neural circuits in the brain,
which function as programs that process information. By altering the
neural circuitry that develops, mutations can alter the information
processing properties of these programs, creating alternative
information-behavior relationships. Selection should retain or discard
alternative circuit designs from a species' neural architecture on the
basis of how well the information-behavior relationships they produce
promote the propagation of the genetic bases of their designs. Those
circuit designs that promote their own proliferation will be retained
and spread, eventually becoming species-typical (or stably
frequency-dependent); those that do not will eventually disappear from
the population. The idea that the evolutionary causation of behavior
would lead to rigid, inflexible behavior is the opposite of the truth:
Evolved neural architectures are specifications of richly contingent
systems for generating responses to informational inputs.
As a result of selection acting on information-behavior relationships,
the human brain is predicted to be densely packed with programs that
cause intricate relationships between information and behavior,
including functionally specialized learning systems, domain-specialized
rules of inference, default preferences that are adjusted by experience,
complex decision rules, concepts that organize our experiences and
databases of knowledge, and vast databases of acquired information
stored in specialized memory systems---remembered episodes from our
lives, encyclopedias of plant life and animal behavior, banks of
information about other people's proclivities and preferences, and so
on. All of these programs and the databases they create can be called on
in different combinations to elicit a dazzling variety of behavioral
responses. These responses are themselves information, subsequently
ingested by the same evolved programs, in endless cycles that produce
complex eddies, currents, and even singularities in cultural life. To
get a genuine purchase on human behavior and society, researchers need
to know the architecture of these evolved programs. Knowing the
selection pressures will not be enough. Our behavior is not a direct
response to selection pressures or to a "need" to increase our
reproduction.
Hence, one of several reasons why evolutionary psychology is distinct
from human sociobiology and other similar approaches lies in its
rejection of fitness maximization as an explanation for behavior
(Cosmides & Tooby, 1987; Daly & Wilson, 1988; Symons, 1987, 1989, 1992;
Tooby & Cosmides, 1990a, 1992). The relative degree of fitness promotion
under ancestral conditions is simply the design criterion by which
alternative mutant designs were sorted in the evolutionary past. (The
causal role fitness plays in the present is in glacially changing the
relative frequencies of alternative designs with respect to future
generations.) Although organisms sometimes appear to be pursuing fitness
on behalf of their genes, in reality they are executing the evolved
circuit logic built into their neural programs, whether this corresponds
to current fitness maximization or not. Organisms are adaptation
executers, not fitness pursuers. Mapping the computational architecture
of the mechanisms will give a precise theory of behavior, while relying
on predictions derived from fitness maximization will give a very
impoverished and unreliable set of predictions about behavioral dynamics.
_______________________________________________
pen-l mailing list
[email protected]
https://lists.csuchico.edu/mailman/listinfo/pen-l
