COMPLEXITY, PROBLEM SOLVING,
AND SUSTAINABLE SOCIETIES,
Joseph A. Tainter, 1996
from GETTING DOWN TO EARTH: Practical
Applications of Ecological Economics, Island Press, 1996; ISBN 1-55963-503-7
Historical knowledge is essential to practical
applications of ecological economics. Systems of problem solving develop greater
complexity and higher costs over long periods. In time such systems either
require increasing energy subsidies or they collapse. Diminishing returns
to complexity in problem solving limited the abilities of earlier societies to
respond sustainably to challenges, and will shape contemporary responses to
global change. To confront this dilemma we must understand both the role of
energy in sustaining problem solving, and our historical position in systems of
In our quest to understand sustainability we
have rushed to comprehend such factors as energy transformations, biophysical
constraints, and environmental deterioration, as well as the human
characteristics that drive production and consumption, and the assumptions of
neoclassical economics. As our knowledge of these matters increases, practical
applications of ecological economics are emerging. Yet amidst these advances
something important is missing. Any human problem is but a moment of reaction to
prior events and processes. Historical patterns develop over generations or
even centuries. Rarely will the experience of a lifetime disclose fully the
origin of an event or a process. Employment levels in natural resource
production, for example, may respond to a capital investment cycle with a lag
time of several decades (Watt 1992). The factors that cause societies to
collapse take centuries to develop (Tainter 1988). To design policies for today
and the future we need to understand social and economic processes at all
temporal scales, and comprehend where we are in historical patterns. Historical
knowledge is essential to sustainability (Tainter 1995a). No program to enhance
sustainability can be considered practical if it does not incorporate such
In this era of global environmental change we
face what may be humanity's greatest crisis. The cluster of transformations
labeled global change dwarfs all previous experiences in its speed. in the
geographical scale of its consequences, and in the numbers of people who will be
affected (Norgaard 1994). Yet many times past human populations faced
extraordinary challenges, and the difference between their problems and ours is
only one of degree. One might expect that in a rational, problem-solving
society, we would eagerly seek to understand historical experiences. In
actuality, our approaches to education and our impatience for innovation have
made us averse to historical knowledge (Tainter 1995a). In ignorance, policy
makers tend to look for the causes of events only in the recent past (Watt
1992). As a result, while we have a greater opportunity than the people of any
previous era to understand the long-term reasons for our problems, that
opportunity is largely ignored. Not only do we not know where we are in history,
most of our citizens and policy makers are not aware that we ought to.
A recurring constraint faced by previous
societies has been complexity in problem solving. It is a constraint that is
usually unrecognized in contemporary economic analyses. For the past 12,000
years human societies have seemed almost inexorably to grow more complex. For
the most part this has been successful: complexity confers advantages, and one
of the reasons for our success as a species has been our ability to 'Increase
rapidly the complexity of our behavior (Tainter 1992, 1995b). Yet complexity can
also be detrimental to sustainability. Since our approach to resolving our
problems has been to develop the most complex society and economy of human
history, it is important to understand how previous societies fared when they
pursued analogous strategies. In this chapter I will discuss the factors that
caused previous societies to collapse, the economics of complexity in problem
solving, and some implications of historical patterns for our efforts at problem
solving today. This discussion indicates that part of our response to global
change must be to understand the long-term evolution of problem-solving systems.
THE DEVELOPMENT OF
is a key concept of this essay. In an earlier
study I characterized it as follows:
Complexity is generally understood to refer to
such things as the size of a society, the number and distinctiveness of its
parts, the variety of specialized social roles that it incorporates, the number
of distinct social personalities present, and the variety of mechanisms for
organizing these into a coherent, functioning whole. Augmenting any of these
dimensions increases the complexity of a society. Hunter-gatherer societies (by
way of illustrating one contrast in complexity) contain no more than a few dozen
distinct social personalities, while modern European censuses recognize 10,000
to 20,000 unique occupational roles, and industrial societies may contain
overall more than 1,000,000 different kinds of social personalities (McGuire
1983; Tainter 1988). 1
As a simple illustration of differences in
complexity, Julian Steward pointed out the contrast between the native peoples
of western North America, among whom early ethnographers documented 3,000 to
6,000 cultural elements, and the U.S. Army, which landed 500,000+ artifact types
at Casablanca in World War 11 (Steward 1955). Complexity is quantifiable.
For over 99% of the history of humanity we lived
as low-density foragers or farmers in egalitarian communities of no more than a
few dozen persons (Carneiro 1978). Leslie White pointed out that such a cultural
system, based primarily on human labor, can generate only about 1/20 horsepower
per capita per year (White 1949, 1959). From this base of undifferentiated
societies requiring small amounts of energy, the development of complex cultural
systems was, a priori, unlikely. The conventional view has been that human
societies have a latent tendency towards greater complexity. Complexity was
assumed to be a desirable thing, and the logical result of surplus food, leisure
time, and human creativity. Although this scenario is popular, it is inadequate
to explain the evolution of complexity. In the world of cultural complexity
there is, to use a colloquial expression, no free lunch. More complex societies
are costlier to maintain than simpler ones and require higher support levels per
capita. A society that is more complex has more sub-groups and social roles,
more networks among groups and individuals, more horizontal and vertical
controls, higher flow of information, greater centralization of information,
more specialization, and greater interdependence of parts. Increasing any of
these dimensions requires biological, mechanical, or chemical energy. In the
days before fossil fuel subsidies, increasing the complexity of a society
usually meant that the majority of its population had to work harder (Tainter
1988, 1992, 1994a, 1995a, 1995b).
Many aspects of human behavior appear to be
complexity averse (Tainter 1995b). The so-called "complexity of modern life" is
a regular complaint in popular discourse. Some of the public discontent with
government stems from the fact that government adds complexity to people's
lives. In science, the Principle of Occam's Razor has enduring appeal because it
states that simplicity in explanation is preferable to complexity.
Complexity has always been inhibited by the
burdens of time and energy that it imposes, and by complexity aversion
(which is no doubt related to cost). Thus explaining why human societies have
become increasingly complex presents more of a challenge than 'Is customarily
thought. The reason why complexity increases is that, most of the time, it
works. Complexity is a problem solving strategy that emerges under conditions of
compelling need or perceived benefit. Throughout history, the stresses and
challenges that human populations have faced have often been resolved by
becoming more complex. While a complete review is not possible here, this trend
is evident in such spheres as:
Foraging and agriculture (Boserup 1965; Clark
and Haswell 1966-1 Asch et al. 1972; Wilkinson 1973; Cohen 1977; Minnis 1995;
Technology (Wilkinson 1973; Nelson 1995);
Competition, warfare, and arms races (Parker
1988; Tainter 1992);
Sociopolitical control and specialization
(Olson 1982; Tainter 1988); and
Research and development (Price 1963; Rescher
1978, 1980; Rostow 1980; Tainter 1988, 1995a).
In each of these areas,
complexity increases through greater differentiation, specialization, and
The development of complexity is thus an
economic process: complexity levies costs and yields benefits. It is an
investment, and it gives a variable return. Complexity can be both beneficial
and detrimental. Its destructive potential is evident in historical cases where
increased expenditures on socioeconomic complexity reached diminishing returns,
and ultimately, in some instances, negative returns (Tainter 1988, 1994b). This
outcome emerges from the normal economic process: simple, inexpensive solutions
are adopted before more complex, expensive ones. Thus, as human populations have
increased, hunting and gathering has given way to increasingly intensive
agriculture, and to industrialized food production that consumes more energy
than it produces (Clark and Haswell 1966; Cohen 1977; Hall et al. 1992).
Minerals and energy production move consistently from easily accessible,
inexpensively exploited reserves to ones that are costlier to find, extract,
process, and distribute. Socioeconomic organization has evolved from egalitarian
reciprocity, short-term leadership, and generalized roles to complex hierarchies
with increasing specialization.
The graph in Figure 4.1 is based on these
arguments. As a society increases in complexity, it expands investment in such
things as resource production, information processing, administration, and
defense. The benefit/cost curve for these expenditures may at first increase
favorably, as the most simple, general, and inexpensive solutions are adopted (a
phase not shown on this chart). Yet as a society encounters new stresses, and
inexpensive solutions no longer suffice, its evolution proceeds in a more costly
direction. Ultimately a growing society reaches a point where continued
investment in complexity yields higher returns, but at a declining marginal
rate. At a point such as B1, C1 on this chart a society has entered the phase
where it starts to become vulnerable to collapse. 
Figure 4.1. Diminishing returns to increasing
complexity (after Tainter 1988).
Two things make a society liable to collapse at
this point. First new emergencies impinge on a people who are investing in a
strategy that yields less and less marginal return. As such a society becomes
economically weakened it has fewer reserves with which to counter major
adversities. A crisis that the society might have survived in its earlier days
now becomes insurmountable.
Second, diminishing returns make complexity less
attractive and breed disaffection. As taxes and other costs rise and there are
fewer benefits at the local level, more and more people are attracted by the
idea of being independent. The society "decomposes" as people pursue their
immediate needs rather than the long-term goals of the leadership. 
As such a society evolves along the marginal
return curve beyond B2, C2, it crosses a continuum of points, such as B1, C3,
where costs are increasing, but the benefits have actually declined to those
previously available at a lower level of complexity. This is a realm of negative
returns to investment in complexity. A society at such a point would find that,
upon collapsing, its return on investment in complexity would noticeably rise. A
society in this condition is extremely vulnerable to collapse.
This argument, developed and tested to explain
why societies collapse (Tainter 1988), is also an account of historical trends
in the economics of problem solving. The history of cultural complexity is the
history of human problem solving. In many sectors of investment, such as
resource production, technology, competition, political organization, and
research, complexity is increased by a continual need to solve problems. As
easier solutions are exhausted, problem solving moves inexorably to greater
complexity, higher costs, and diminishing returns. This need not lead to
collapse, but it is important to understand the conditions under which it might.
To illustrate these conditions it is useful to review three examples of
increasing complexity and costliness in problem solving: the collapse of the
Roman Empire, the development of industrialism, and trends in contemporary
The Collapse of The Roman
One outcome of diminishing returns to complexity
is illustrated by the collapse of the Western Roman Empire. As a solar-energy
based society which taxed heavily, the empire had little fiscal reserve.
When confronted with military crises, Roman Emperors often had to respond by
debasing the silver currency (Figure 4.2) and trying to raise new funds. In the
third century A.D. constant crises forced the emperors to double the size of
the army and increase both the size and complexity of the government. To pay for
this, masses of worthless coins were produced, supplies were commandeered from
peasants, and the level of taxation was made even more oppressive (up to
two-thirds of the net yield after payment of rent). Inflation devastated the
economy. Lands and population were surveyed across the empire and assessed for
taxes. Communities were held corporately liable for any unpaid amounts. While
peasants went hungry or sold their children into slavery, massive fortifications
were built, the size of the bureaucracy doubled, provincial administration was
made more complex, large subsidies in gold were paid to Germanic tribes, and new
imperial cities and courts were established. With rising taxes, marginal lands
were abandoned and population declined. Peasants could no longer support large
families. To avoid oppressive civic obligations, the wealthy fled from cities to
establish self-sufficient rural estates. Ultimately, to escape taxation,
peasants voluntarily entered into feudal relationships with these land holders.
A few wealthy families came to own much of the land in the western empire, and
were able to defy the imperial government. The empire came to sustain itself by
consuming its capital resources; producing lands and peasant population (Jones
1964, 1974; Wickham 1984; Tainter 1988, 1994b). The Roman Empire provides
history's best-documented example of how increasing complexity to resolve
problems leads to higher costs, diminishing returns, alienation of a support
population, economic weakness, and collapse. In the end it could no longer
afford to solve the problems of its own existence.
Figure 4.2. Debasement of the Roman silver
currency, 0-269 A.D. (after Tainter 1994b with modifications). The chart shows
grams of silver per denarius (the basic silver coin) from 0 to 237 A.D., and per
1/2 denarius from 238-269 A.D. (when the denarius was replaced by a larger coin
tariffed at two denarii).
Population, Resources, and
The fate of the Roman Empire is not the
unavoidable destiny of complex societies. It is useful to discuss a historical
case that turned out quite differently. In one of the most interesting works of
economic history, Richard Wilkinson (1973) showed that in late-and post-medieval
England, population growth and deforestation stimulated economic development,
and were at least partly responsible for the Industrial Revolution. Major
increases in population, at around 1300, 1600, and in the late 18th century, led
to intensification in agriculture and industry. As forests were cut to provide
agricultural land and fuel for a growing population, England's heating, cooking,
and manufacturing needs could no longer be met by burning wood. Coal came
to be increasingly important, although it was adopted reluctantly. Coal
was costlier to obtain and distribute than wood, and restricted in its
occurrence. It required a new, costly distribution system. As coal gained
importance in the economy the most accessible deposits were depleted. Mines had
to be sunk ever deeper, until groundwater came to be a problem. Ultimately, the
steam engine was developed and put to use pumping water from mines. With
the development of a coal-based economy, a distribution system, and the steam
engine, several of the most important technical elements of the Industrial
Revolution were in place. Industrialism, that great generator of economic
well-being, came in part from steps to counteract the consequences of resource
depletion, supposedly a generator of poverty and collapse. Yet it was a system
of increasing complexity that did not take long to show diminishing returns in
some sectors. This point will be raised again later.
Science and Problem Solving
Contemporary science is humanity's greatest
exercise in problem solving. Science is an institutional aspect of society, and
research is an activity that we like to think has a high return. Yet as
generalized knowledge is established early in the history of a discipline, the
work that remains to be done is increasingly specialized. These types of
problems tend to be increasingly costly and difficult to resolve, and on average
advance knowledge only by small increments (Rescher 1978, 1980; Tainter 1988).
Increasing investments in research yield declining marginal returns.
Some notable scholars have commented upon this.
Walter Rostow once argued that marginal productivity first rises and then
declines in individual fields (1980). The great physicist Max Planck, in a
statement that Nicholas Rescher calls 'Planck's Principle of Increasing Effort,
observed that "...with every advance [in science] the difficulty of the task is
increased" (Rescher 1980). As easier questions are resolved, science moves
inevitably to more complex research areas and to larger, costlier organizations
(Rescher 1980). Rescher suggests that "As science progresses within any of its
specialized branches, there is a marked increase in the overall resource-cost to
realizing scientific findings of a given level [of] intrinsic significance..."
(1978). Exponential growth in the size and costliness of science is necessary
simply to maintain a constant rate of progress (Rescher 1980). Derek de
Solla Price noted that in 1963 science was, even then, growing faster than
either the population or the economy, and of all scientists who had ever lived,
80-90% were still alive at the time of his writing (Price 1963). In the same
period, such matters prompted Dael Wolfle to publish a query in Science
titled "How Much Research for a Dollar?" (Wolfle 1960).
Scientists rarely think about the benefit/cost
ratio to investment in their research. Yet if we assess the productivity of our
investment in science by some measure such as the issuance of patents (Figure
4.3), the productivity of certain kinds of research appears to be declining.
Patenting is a controversial indicator among those who study such matters (Machlup
1962; Schmookler 1966; Griliches 1984), and does not by itself indicate the
economic return to the expenditures. Medicine is a field of applied science
where the return to investment can be determined more readily. Over the 52-year
period shown in Figure 4.4, from 1930-1982, the productivity of the United
States health care system for improving life expectancy declined by nearly 60%.
The declining productivity of the United States
health care system illustrates clearly the historical development of a
problem-solving field. Rescher (1980) points out: Once all of the findings at a
given state-of-the-art level of investigative technology have been realized, one
must move to a more expensive level.... In natural science we are involved in a
technological arms race: with every victory over nature the difficulty of
achieving the breakthroughs which lie ahead is increased.
The declining productivity of medicine is due to
the fact that the inexpensive diseases and ailments were conquered first (the
basic research that led to penicillin costing no more than $20,000), so that
those remaining are more difficult and costly to resolve (Rescher 1978). And as
each increasingly expensive disease is conquered, the increment to average life
expectancy becomes ever smaller.
Figure 4.3. Patent applications in respect to
research inputs, 1942-1958 (data from Machlup 1962)
Figure 4.4. Productivity of the U.S. health
care system, 1930-1982 (data from Worthington 1975; U.S. Bureau of Census 1983).
Productivity index = (Life expectancy)/(National health expenditures as percent
Implications of the Examples
The Roman Empire, industrialism, and science are
important, not only for their own merits, but also because they exemplify: (1)
how problem solving evolves along a path of increasing complexity, higher costs,
and declining marginal returns (Tainter 1988), and (2) some different outcomes
of that process. In the next section, I discuss what these patterns imply for
our efforts to address contemporary problems.
PROBLEM SOLVING, ENERGY, AND
This historical discussion gives a perspective
on what it means to be practical and sustainable. A few years ago I described
about two dozen societies that have collapsed (Tainter 1988). In no case is it
evident or even likely that any of these societies collapsed because its members
or leaders did not take practical steps to resolve its problems (Tainter 1988).
The experience of the Roman Empire is again instructive. Most actions that the
Roman government took in response to crises-such as debasing the currency,
raising taxes, expanding the army, and conscripting labor-were practical
solutions to immediate problems. It would have been unthinkable not to adopt
such measures. Cumulatively, however, these practical steps made the empire ever
weaker, as the capital stock (agricultural land and peasants) was depleted
through taxation and conscription. Over time, devising practical solutions drove
the Roman Empire into diminishing, then negative, returns to complexity. The
implication is that to focus a problem-solving system, such as ecological
economics, on practical applications will not automatically increase its value
to society, nor enhance sustainability. The historical development of
problem-solving systems needs to be understood and taken into consideration.
Most who study contemporary issues certainly
would agree that solving environmental and economic problems requires both
knowledge and education. A major part of our response to current problems has
been to increase our level of research into environmental matters, including
global change. As our knowledge increases and practical solutions emerge,
governments will implement solutions and bureaucracies will enforce them. New
technologies will be developed. Each of these steps will appear to be a
practical solution to a specific problem. Yet cumulatively these practical steps
are likely to bring increased complexity, higher costs, and diminishing returns
to problem solving.' Richard Norgaard has stated the problem well: "Assuring
sustainability by extending the modem agenda ... will require, by several orders
of magnitude, more data collection, interpretation, planning, political
decision-making, and bureaucratic control" (Norgaard 1994).
Donella Meadows and her colleagues have given
excellent examples of the economic constraints of contemporary problem solving.
To raise world food production from 1951-1966 by 34%, for example, required
increasing expenditures on tractors of 63%, on nitrate fertilizers of 146%, and
on pesticides of 300%. To remove all organic wastes from a sugar-processing
plant costs 100 times more than removing 30%. To reduce sulfur dioxide in the
air of a U.S. city by 9.6 times, or particulates by 3.1 times, raises the cost
of pollution control by 520 times (Meadows et al. 1972). All environmental
problem solving will face constraints of this kind.
Bureaucratic regulation itself generates
further complexity and costs. As regulations are issued and taxes
established, those who are regulated or taxed seek loopholes and lawmakers
strive to close these. A competitive spiral of loophole discovery and closure
unfolds, with complexity continuously increasing (Olson 1982). In these days
when the cost of government lacks political support, such a strategy is
unsustainable. It is often suggested that environmentally benign behavior should
be elicited through taxation incentives rather than through regulations. While
this approach has some advantages, it does not address the problem of
complexity, and may not reduce overall regulatory costs as much as is thought.
Those costs may only be shifted to the taxation authorities, and to the society
as a whole.
It is not that research, education, regulation,
and new technologies cannot potentially alleviate our problems. With enough
investment perhaps they can. The difficulty is that these investments will be
costly, and may require an increasing share of each nation's gross domestic
product. With diminishing returns to problem solving, addressing environmental
issues in our conventional way means that more resources will have to be
allocated to science, engineering, and government. In the absence of high
economic growth this would require at least a temporary decline in the standard
of living, as people would have comparatively less to spend on food, housing,
clothing, medical care, transportation, and entertainment.
To circumvent costliness in problem solving it
is often suggested that we use resources more intelligently and efficiently.
Timothy Allen and Thomas Hoekstra, for example, have suggested that in managing
ecosystems for sustainability, managers should identify what is missing from
natural regulatory process and provide only that. The ecosystem will do the
rest. Let the ecosystem (i.e., solar energy) subsidize the management effort
rather than the other way around (Allen and Hoekstra 1992). It is an intelligent
suggestion. At the same time, to implement it would require much knowledge that
we do not now possess. That means we need research that is complex and costly,
and requires fossil-fuel subsidies. Lowering the costs of complexity in one
sphere causes them to rise in another.
Agricultural pest control illustrates this
dilemma. As the spraying of pesticides exacted higher costs and yielded
fewer benefits, integrated pest management was developed. This system relies on
biological knowledge to reduce the need for chemicals, and employs monitoring of
pest populations, use of biological controls, judicious application of
chemicals, and careful selection of crop types and planting dates (Norgaard
1994). It is an approach that requires both esoteric research by scientists and
careful monitoring by farmers. Integrated pest management violates the principle
of complexity aversion, which may partly explain why it is not more widely used.
Such issues help to clarify what constitutes a
sustainable society. The fact that problem-solving systems seem to evolve to
greater complexity, higher costs, and diminishing returns has significant
implications for sustainability. In time, systems that develop in this way are
either cut off from further finances, fail to solve problems, collapse, or come
to require large energy subsidies. This has been the pattern historically in
such cases as the Roman Empire, the Lowland Classic Maya, Chacoan Society of the
American Southwest, warfare in Medieval and Renaissance Europe, and some aspects
of contemporary problem solving (that is, in every case that I have investigated
in detail) (Tainter 1988, 1992, 1994b, 1995a). These historical patterns suggest
that one of the characteristics of a sustainable society will be that it has a
sustainable system of problem solving-one with increasing or stable returns, or
diminishing returns that can be financed with energy subsidies of assured
supply, cost, and quality.
Industrialism illustrates this point. It
generated its own problems of complexity and costliness. These included railways
and canals to distribute coal and manufactured goods, the development of an
economy increasingly based on money and wages, and the development of new
technologies. While such elements of complexity are usually thought to
facilitate economic growth, in fact they can do so only when subsidized by
energy. Some of the new technologies, such as the steam engine,
showed diminishing returns to innovation quite early in their development
(Wilkinson 1973; Giarini and Louberge 1978; Giarini 1984). What set
industrialism apart from all of the previous history of our species was its
reliance on abundant, concentrated, high-quality energy (Hall et al. 1992). 5
With subsidies of inexpensive fossil fuels, for a long time many consequences of
industrialism effectively did not matter. Industrial societies could afford
them. When energy costs are met easily and painlessly, benefit/cost ratio to
social investments can be substantially ignored (as it has been in contemporary
industrial agriculture). Fossil fuels made industrialism, and all that flowed
from it (such as science, transportation, medicine, employment, consumerism,
high-technology war, and contemporary political organization), a system of
problem solving that was sustainable for several generations.
Energy has always been the basis of cultural
complexity and it always will be. If our efforts to understand and resolve
such matters as global change involve increasing political, technological,
economic, and scientific complexity, as it seems they will, then the
availability of energy per capita will be a constraining factor. To increase
complexity on the basis of static or declining energy supplies would require
lowering the standard of living throughout the world. In the absence of a clear
crisis very few people would support this. To maintain political support for our
current and future investments in complexity thus requires an increase in the
effective per capita supply of energy-either by increasing the physical
availability of energy, or by technical, political, or economic innovations that
lower the energy cost of our standard of living. Of course, to discover such
innovations requires energy, which underscores the constraints in the
This chapter on the past clarifies potential
paths to the future. One often-discussed path is cultural and economic
simplicity and lower energy costs. This could come about through the "crash"
that many fear-a genuine collapse over a period of one or two generations, with
much violence, starvation, and loss of population. The alternative is the "soft
landing" that many people hope for-a voluntary change to solar energy and green
fuels, energy-conserving technologies, and less overall consumption. This is a
utopian alternative that, as suggested above, will come about only if severe,
prolonged hardship in industrial nations makes it attractive, and if economic
growth and consumerism can be removed from the realm of ideology.
The more likely option is a future of greater
investments in problem solving, increasing overall complexity, and greater use
of energy. This option is driven by the material comforts it provides, by vested
interests, by lack of alternatives, and by our conviction that it is good. If
the trajectory of problem solving that humanity has followed for much of the
last 12,000 years should continue, it is the path that we are likely to take in
the near future.
Regardless of when our efforts to understand and
resolve contemporary problems reach diminishing returns, one point should be
clear. It is essential to know where we are in history (Tainter 1995a). If
macroeconomic patterns develop over periods of generations or centuries, it is
not possible to comprehend our current conditions unless we understand where we
are in this process. We have the the opportunity to become the first people in
history to understand how a society's problem-solving abilities change. To know
that this is possible yet not to act upon it would be a great failure of the
practical application of ecological economics.
This- chapter is revised from a plenary address
to the Third International Meeting of the International Society for Ecological
Economics, San Jose, Costa Rica, 28 October 1994. 1 am grateful to Cutler J.
Cleveland, Robert Costanza, and Olman Segura for the invitation to present the
address, to Maureen Garita Matamoros for assistance during the conference, to
Denver Burns, John Faux, Charles A. S. Hall, Thomas Hoekstra, Joe Kerkvliet, and
Daniel Underwood for comments on the plenary address, and to Richard Periman and
Carol Raish for reviewing this version.
In some literature of the physical sciences,
striving for a definition as objective as possible, the complexity of a system
is considered to be the length of a description of its regularities (Gell-Mann
1992, 1994). This is compatible with the definition employed here. A society
with fewer parts, less differentiated parts, and fewer or simpler integrative
systems can certainly be described more succinctly than can a society with
more of these (Tainter 1995b).
Collapse is a rapid transformation to a lower
degree of complexity, typically involving significantly less energy
consumption (Tainter 1988).
This is part of the process responsible for
contemporary separatist movements in the U.S.
I have not considered so-called "green"
alternatives in this analysis. There are two reasons why these appear to be
impractical in the short-term. Firstly, industrial economies are closely
coupled to the existing production system and resource base, including
conventional energy (Hall et al. 1992; Watt 1992). The capital costs of
massive, rapid industrial conversion would be very high. Secondly, experience
since 1973 indicates that most members of industrial societies will not change
their consumption patterns merely because of abstract projections about the
long-term supply of energy or other resources. They will do so only when the
prices of energy, and of goods and services that rely on energy, rise sharply
for an extended time. It takes protracted hardship to convince people that the
world to which they have been accustomed has changed irrevocably. Hardship
that is minor or episodic merely allows leaders to exploit popular discontent
for personal gain. Economic growth has become mythologized as part of our
ideology, which makes it particularly difficult to discuss objectively in the
public arena (Giarini and Louberge 1978).
Coal of course was not the only element that
promoted industrialism. Other factors included declining supplies of fuelwood
(Wilkinson 1973), changes in land-use laws. and availability of laborers who
could be employed in manufacturing.
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