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Bounded
Rationality, Institutionalism, and Functionalism
Simon's description of the real-world
market-determined price system as pragmatic and as
an institution places him in the worthy intellectual
company of the American Institutionalist school of
economic thought, even though he does not identify
himself as such.
Therefore, a few background comments about
this school of economics and about its principal
advocates are in order.
In the "Introduction" to his Types
of Economic Theory the Institutionalist
economist Wesley Clair Mitchell says that there have
been different types of economic theory, not only
because there have been different types of problems,
but also because there have been different
conceptions of human nature.
At issue is the neoclassicals’ concept of
human nature, which motivated them to construct a
deductive theoretical economics based on the
rationality postulates. The American
Institutionalist School was founded as a revolt
within the American economic profession, which
rejected the formal and abstract deductivism in
neoclassical economics and instead appealed to
experience. It
had its roots in the Pragmatist philosophy, the only
philosophy indigenous to the United States, which
itself was a revolt in the American philosophy
profession, and which rejected the natural-law and
utilitarian traditions in European academic
philosophy.
The founding father of American
Institutionalism is the iconoclastic economist and
somewhat eccentric individual, Thorstein Veblen
(1857-1929). In
his "Why is Economics not an Evolutionary
Science?" in his
The Place of Science in Modern Civilization
(1919) Veblen characterized the neoclassical
economists' hedonistic psychology as describing man
as a "lightening calculator" of pleasures
and pains, who passively responds to his environment
and is unchanged by the environment.
Veblen rejected this conception of human
nature and proposed instead an anthropological
conception, in which the individual's psychology is
formed by institutions prevailing in the community
in which a man lives, and most notably institutions
which evolve. He
also therefore proposed that economics itself is an
evolutionary science that employs a
"genetic" type of theory, which describes
the cumulative cultural growth of economic
institutions, instead of the "taxonomic"
type of theory used by neoclassical economists such
as the Austrian school. He rejects the Austrian's ad
hoc attempts to save their natural-law
explanations from deviant facts by invoking
"disturbing factors.”
He also explicitly references Charles Darwin,
and rejects the German Historicist School as
pre-Darwinist for offering only enumeration of data
and narrative accounts instead of genetic theory.
Another noteworthy representative of American
Institutionalism is John R. Commons (1862-1945).
In his Institutional
Economics (1934) Commons states explicitly that
he is following the Pragmatist philosophy of Charles
S. Peirce.
In the second volume of this book Commons
discusses Weber's ideal-type concepts, and he
criticizes their fixed and unchanging character.
Commons states that the utopian character of
the ideal type only becomes more utopian as
scientific investigation advances.
Instead of the ideal type, Commons proposes
the “changeable hypothesis", that takes into
account new factors revealed to be relevant in the
investigation, and that retires from consideration
old factors found to be irrelevant. This amounts to
demanding that economics be more empirical.
Weber had explicitly denied that the ideal
type is a hypothesis.
Commons says that use of hypotheses makes
less utopian the utopias that our minds create.
Commons does not explicitly propose revising
the maximizing assumption in the neoclassical
rationality postulate; he rejects it.
A typical Institutionalist, he maintains that
in addition to economic interactions described by
neoclassical economics there are other, namely
institutional, factors that are also operative in
determining the outcomes of economic transactions.
In both his earlier works and again in his
final work, The Economics
of Collective Action (1950, 1970), he proposes a
more adequate psychology, which he calls a "negotiational
psychology" as opposed to the hedonist
psychology of the utilitarians.
He also calls it an objective and
behavioristic psychology instead of the subjective
psychology of pain and pleasure, because it is the
psychology of language, duress, coercion,
persuasion, command, obedience, propaganda, and a
psychology of physical, economic, and moral powers. He therefore distinguishes three types of transactions: (1)
bargaining transactions, which occur in the market,
and which is the type treated in neoclassical
economic theory, (2) managerial transactions, which
occur between levels in organizational hierarchies,
and (3) rationing transactions, which are agreements
about apportioning, such as occur in budgeting
decisions. He
says that all three types have "futurity",
that is, they require some security that future
outcomes occur as expected by the participants, so
that expectations can operate as working rules.
He sees the three types as functionally
interdependent.
The Institutionalist perspective focuses on
the second and third types of transactions, because
these represent “collective action in control of
individual action”, which is Commons’ explicit
definition of Institutionalism.
Commons was particularly interested in the
social control exercised by courts over the working
rules in bargaining transactions.
Perhaps it is not coincidental to Commons’
interests that in the 1930’s before the Roosevelt
Administration, the courts viewed collective
bargaining by labor unions as an illegal conspiracy
against trade. The second and third types of transactions, however, are the
ones relevant to Simon’s interests.
Simon elaborates on the relation of
institutions to his thesis of satisficing bounded
rationality in his “Rationality as Process and as
Product of Thought" (1978) reprinted in his Models
of Bounded Rationality.
He does not explicitly refer to the academic
literatures of either Pragmatist philosophy or
Institutionalist economics, but instead draws upon
the "functionalist" type of explanation
often found in the sociological literature.
He references the Encyclopedia
of the Social Sciences (1968) in which
functionalism is defined as an explanation of how
major social patterns operate to maintain the
integration or adaptation of larger social systems.
More formally stated functional explanations
are about movements of a system toward stable
self-maintaining equilibriums. Most notably Simon states that there is no reason to suppose
that the attained equilibria are global maxima.
In other words, functional explanation
describes satisficing behavior.
In this paper he furthermore maintains that
functional analyses are not focused on quantitative
magnitudes as are found in price theory, but are
focused on qualitative and structural questions, and
typically on the choice among a small number of
discrete institutional alternatives.
Particular institutional structures or
practices are seen to entail certain desirable or
undesirable consequences.
A shift in the balance of consequences, or in
the awareness of them, may motivate a change in
institutional arrangements.
Like economic sociologists, who recognize the
underlying role of economic institutions, Simon
argues that economists have in fact not actually
limited themselves to maximization analyses, but
have utilized such qualitative functional analyses
when they seek to explain institutions and behavior
that lie outside the domain of price theory,
distribution, and production.
In his autobiography he says most of the
conclusions drawn by neoclassical economists do not
depend on the assumption of perfect rationality, but
derive from auxiliary institutional assumptions that
are required, in order to reach any conclusions at
all. And
in his Reason in Human Affairs (1983) he says that markets do not operate
in a vacuum, but are part of a larger framework of
social institutions, which provide the stable
environment that makes rationality possible by
supplying reliable patterns of events.
In "Rationality as Process..."
Simon states that the characterization of an
institution is almost never arrived at deductively
from consideration of the function that it must
perform for system survival. Functional analysis is not deductive like theoretical
neoclassical economics.
Rather an institution is a behavior pattern
that is empirically observed, and existence of the
pattern occasions the question of why it persists,
that is, what function it performs.
Institutions can be observed in every
society, and their existence is then rationalized by
the argument that its function is requisite.
But Simon comments that this kind of
reasoning may demonstrate that a particular
behavioral pattern is a sufficient condition for
performing an essential social function, but cannot
demonstrate that the particular pattern is a
necessary condition.
Alternative patterns may be functionally
equivalent, since they serve the same need.
In other words there may be many alternative
satisficing institutional patterns for accomplishing
the same social goal.
Human
Problem Solving, Cognitive Psychology and Heuristics
Simon's theory of procedural rationality is
his theory of human problem solving, and it is
elaborately set forth in his Human
Problem Solving (1972) co-authored with Allen
Newell. This
nine-hundred page magnum
opus took fourteen years to write.
During this period Simon also wrote a briefer
statement, Sciences of the Artificial (1969), and several articles since
reprinted in his Models
of Discovery (1977), an anthology of many of his
previously published papers.
Much of Human
Problem Solving consists of detailed
descriptions of problem-solving computer programs,
none of which pertain to scientific discovery.
Nonetheless his views on human problem
solving are relevant to methodology of science,
because he considers scientific discovery to be a
special case of human problem solving.
At the outset of Human Problem Solving the two collaborating authors state that their
aim is to advance understanding of how humans think
by setting forth a theory of human problem solving.
The concluding section of the book sets forth
a general statement of their theory, which is based
on the computer programs described in the body of
the book and presented as empirical evidence
relevant to their theory.
They state that the specific opportunity
which has set the course for their book is the
development of a science of information processing,
more recently called computer science.
Their central thesis is that explanation of
thinking can be accomplished by means of an
information theory, and that their theory views a
human as a processor of information, an information
processing system.
They say that such a description of the human
is not just metaphorical, because an abstract
concept has been developed of an information
processor, which abstracts from the distinctively
mechanical aspects of the computer. The authors compare the explanations in information science
to the use of differential equations in other sciences
such as classical physics.
An information theory consisting of computer
programs is dynamic like differential equations,
because it describes change in a system through
time. Such
a theory describes the time course of behavior,
characterizing each new act as a function of the
immediately preceding state of the system and its
environment. Given
at any time the memory contents characterizing the
system's state at that moment, the program
determines how the memory contents will change
during the next computing cycle and what the
contents will be at the end of the cycle.
The fundamental methodological problems of
theory construction and theory testing are the same
in the two types of theory.
The theory is tested by providing a specific
set of initial and boundary conditions for the
system, by using the equations or program to predict
the resulting time path, and by comparing this
predicted path with the actual path of the system.
The advantage of an information-processing
language over the mathematical languages for
formulating a theory of thinking is that an
information processing language takes symbolic
structures rather than numbers as values of its
variables.
The information theory about human thinking
and problem solving is a theory in cognitive
psychology. Newell
and Simon note that their theory is concerned with
performance, specifically with the performance of
intelligent adults in our own culture, while
psychologists have traditionally been more concerned
with learning.
In his autobiography as well as elsewhere
Simon distinguishes cognitive psychology from both
the gestalt
and the behavioristic approaches to psychology.
He rejects the black-box approach of the
behaviorists and especially of B.F. Skinner, who
maintains that the black box is empty.
Simon also rejects the reductionist version
of behaviorism, according to which complex behavior
must be explained in terms of neurological
processes, and he also rejects the neurological
modeling approach of the psychologists who use
parallel connectionist networks or neural nets for
computerized explanations.
Newell and Simon propose a theory of symbols
located midway, as it were, between complex
behavioral processes and neurological processes.
Simon acknowledges a debt to the Gestaltists
and their allies, who also recognize a layer of
constructs between behavior and neurology, but Simon
rejects the Gestaltists' wholistic approach to these
constructs. Simon
proposes an explicitly mechanistic type of
explanation of human thinking and problem solving in
terms of information processing.
Simon defines human thinking as a system of
elementary information processes, organized
hierarchically and executed serially.
Simon relies on the concept of hierarchy as a
strategy for managing complexity.
He defines a hierarchical system as one that
is composed of interrelated subsystems, each of
which in turn is hierarchical in structure down to a
lowest level consisting of an elementary subsystem.
In human problem solving hierarchy is
determined by the organization of subgoals, which is
the second idea that Simon said is basic to his
entire scientific output.
Hierarchical organization is common in
computer systems; applications programs are written
in compiler and interpreter languages such as FORTRAN
and BASIC, and these languages in turn contain reserved words that are
names for macros, which are subsystems in the
compiler library, which in turn contain lower level
subsystems, and so on down to a basic level
consisting of elementary systems in binary code.
For the specifically problem-solving type of
human thinking Simon has analyzed information
processing into a few basic concepts. The first of these is the "task environment", by
which he means the problem-solving processor's outer
environment as viewed by the problem solver to
produce a "problem space", together with
the goal that orients the problem solver to his task
environment. The
problem space is the inner environment consisting of
the processor's internal representation of the outer
task environment, and in which the problem solving
activities take place.
Simon maintains that there is no objective
representation of the task environment independently
of some processor's problem space.
Furthermore it is the task or goal that
defines the "point of view" about the
problem-solving processor's outer environment, and
that therefore defines the problem space.
Simon calls this defining process an
"input translation process.” Thirdly in addition to task environment and problem space,
Simon introduces the concept of "method.”
A method is a process that bears some
"rational" relation to attaining a problem
solution, as formulated and seen in terms of the
internal representation, which is the problem space.
Here the term "rational" is
understood as satisficing in the sense that a
satisfactory as opposed to an optimal solution is
achieved. In
the mechanical processor, the method is the computer
program, and most of Simon's theory of problem
solving pertains to the method.
Simon distinguishes three types of method.
The first is the recognition method, which can be
used when the solution is already in the processor's
memory, and artificial-intelligence systems using
this method rely on large stores of specific
information. Computer
programs using this type of method contain a
conditional form of statement, which Simon calls a
"production.”
In a production, whenever the initial
conditions are satisfied, the consequent action is
taken. And
when the conditions of several alternative
productions are satisfied, the conflicts between
them are resolved by priority rules.
In his autobiography Simon notes that
productions have become widely accepted to explain
how human experts make their decisions by
recognizing familiar cues directly, and that
productions have been used for the "expert
systems" in artificial intelligence.
Experts, both human and mechanical, do much
of their problem solving not by searching
selectively, but simply by recognizing the relevant
cues in situations similar to those experienced
before. It
is their wealth of experience that makes them
experts. The
second type of method is what Simon calls the
generate-and-test method.
In this method the computer system generates
a problem space, and has as its goal to find or to
produce a member in a subspace identified as a
solution by a test.
The generality and weakness of this method
lies in the fact that the generation and test
procedures are independent, so that the amount of
search is very large.
Simon typically portrays this method as
requiring a search that is so large, that it cannot
be carried out completely, and so must proceed in a
random manner. To address this problem of
innumerable possibilities the Pragmatist philosopher
C.S. Peirce had advanced his logic of abduction,
which postulates a natural light or instinctive
genius for producing correct theories. Simon advances instead his theory of heuristics, the third
type of problem-solving method, which exploits the
information in the task environment as that task
environment is represented internally in the
processor by the problem space.
In the heuristic search, unlike the
generate-and-test method, there is a dependence of
the search process upon the nature of the object
being sought in the problem space and the progress
being made toward it.
This dependence functions as a feed back that
guides the search process with controlling
information acquired in the process of the search
itself, as the search explores the internalized task
environment. This
method is much more efficient than the
generate-and-test method, and it explains how
complex problems are solved with both human and
mechanical bounded rationality.
These alternative methods represent different
artificial-intelligence research programmes,
software development vs hardware development, which
may also be characterized as knowledge vs speed.
The generate-and-test method is dependent on
fast hardware; the heuristic search method is
dependent on efficient software design. Researchers
preferences for one or another of the methods are
affected by developments in hardware technology, as
well as the magnitude of the problems they select.
The hardware preference has been called the
"brute force" approach, and as the
technology has advanced, it has enabled the
implementation of artificial-intelligence systems
that offer little new software but greatly improved
performance for the extensive searching of very
large problem spaces.
For example the Wall
Street Journal (30 April 1990) reported that a
group of five Carnegie-Mellon University graduate
students with IBM Corporation funding have developed
a multiprocessor chess-playing system named
"Deep Thought", that exhibits grand-master
performance with superhuman speed.
It was reported that this system does not
represent any noteworthy software development either
in chess-playing search heuristics or in expert
chess-playing strategies.
Instead it explores the huge chess-playing
problem space more quickly and extensively than can
the human grand master, who is limited by human
bounds to his rationality.
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