This paper was
published
in 2005; but it's hard to find for free. Here is a shortened, slightly
updated version.
For millennia, humans from diverse cultures have used oracles and omens to try
to read the future. Science and mathematics have long contributed to this
effort, originally through astronomy but now by supercomputers allied to theories
and datasets. For a while, the universe was likened to an enormous mechanical
clock, and a conceit arose that with sufficient data, theory, and computational
power, science might one day refine predicting human affairs to a high accuracy.
More recent discoveries of relativity, quantum mechanics, and chaos theory show
the fallacy of this thinking, even challenging precise astronomic forecasts.
Postmodernism has questioned other fundamentals, so that definitive
statements about even the present can seem audacious. However, the quest for
the perfect should not obstruct the search of the helpful. The failure to
develop a widely accepted science of history does not negate the existence of
useful and durable historical principles; the fact that the future can never be
known with certainty does not mean that little of value can be said about it.
The futurist and systems thinker
Hartmut Bossel has usefully likened the
range of future possibilities as constrained within ‘‘riverbeds’’ of
likelihood. Many properties of human and natural systems compose these
riverbanks. As well as the laws and principles of physics, genetics, biology,
evolution etc, perhaps the most fundamental determinant of the future is that
it must evolve from the present. This means not only that future human society
will be strongly influenced by current and recent economic and social trends
and theories, but also that past alliances, injustices, resentments, and enmity
cannot be wished away. Historical facts, transmitted in the culture and contained
within the psychology and memory of billions of people, will inevitably
influence the future. There are a myriad of such facts and memories, and
together they act to significantly restrict the range of possible futures.
Similarly, existing institutions—social conventions, interpersonal networks,
rules, agencies of government, markets, laws, and norms—are embedded in the
memory, customs, and behavior of the 7.2 billion souls currently alive.
Institutions change, but their rate of change is slowed by the complex
conceptual, legal, and psychological elements through which change must be
filtered. Other identifiable riverbed components include demographic and
infrastructural inertia and the plausible rate of technologic evolution. For
example, barring calamity, such as nuclear war or an asteroid impact, the human
population in 2020 will inevitably be larger than 7.5 billion. Similarly, there
are maximal rates of technologic transition, such as the development and
diffusion of a solar- and hydrogen-fueled energy system that cannot be
plausibly exceeded. Though daunting, the generation of plausible futures is not
impossible, and many spheres of science—especially physical, ecologic, and
social—have made and will continue to make important contributions to this
developing field. Perhaps one day scientific disciplines of both the future and
history will be mature and respected.
Scenarios
All humans build scenarios and create mental models of the future. We all
know that the sun will rise tomorrow, and we project many other elements of the present into the
short-term future, such our plans for a holiday or even retirement. But as the
length of focus and the variety of possible outcomes increase, confidence we
can have in our projections diminishes rapidly.
Some futurists imagine a world of extremely rapid technological innovation and
transformation. It is possible to conceive of a future full of energy- and
greenhouse gas emission–sparing devices, of new crops that reduce cultivation
pressure on marginal land, of techniques that harness biology to large-scale
industrial processes, and of new forms of communication that enable the rapid
diffusion of information, literacy, and education. Such visions can then be
used to forecast optimistic rates of hunger alleviation, of slowed greenhouse
gas accumulation, of adequate water quantity and quality, and so on.
Lay scenarios and social thresholds
Planning, whether for the next hunt, crop or corporate takeover, is an ancient
human characteristic and has often formed the basis for attempts to enlist
celestial help. In well-governed societies, sophisticated economic and social
planning is routine. As large as the formal scenario literature is, an even
larger mass of lay scenarios exists within people's imagination. The collective
imagination of the near-term future by large numbers of people can sometimes
mobilize society in ways that significantly influence that future, such as by
large-scale protests and revolution.
In some cases, social thresholds are passed that are beneficial to society,
freedom, and population health. For example, the peace movements in Western
countries in the 1980s arose in part because millions of ordinary people became
sufficiently concerned about a potential nuclear Armageddon (a lay scenario) to
vehemently protest. In turn, this reduced the risk of global nuclear war.
Shortly after, mass social movements in Eastern Europe led to the peaceful fall
of several governments.
In other cases, such as the 1989
Tiananmen Square
protest in Beijing, collective imagination proved, premature. The
Rwandan genocide of 1994, when
one-sixth of the country’s population was rapidly slaughtered, illustrates the passing
of a social threshold that was immensely damaging to population health.
Although this event may seem an inexplicable example of barbarity, other
workers have suggested that the genocide was in fact a foreseeable and
understandable consequence of resentment and resource scarcity leavened by the
rapid growth in the number of largely unemployed, landless, manipulable, and
desperate
young men.
Problems with existing scenarios
Large-scale thresholds, whether social or environmental, are problems for
scenario maker. These thresholds that lead to the quantitatively and
qualitatively altered post-threshold states are hard to predict. Though their nature
is uncertain and contested, their occurrence is well understood, not only by
scenario workers, but also by the lay public. Evidence for this exists in the
plethora of sayings in many languages and cultures, such as ‘‘a chain is only
as strong as its weakest link’’ and ‘‘it is the last straw that breaks the camel’s
back.’’
Most scenario builders work in groups, and reaching a consensus about the scale
and timing of thresholds introduces another difficulty. This may be complicated
by a wish to not appear too negative, because of the risk of marginalization of
more pessimistic forecasts, such as the
Limits to Growth or those from
Lester Brown.
The precise prediction of most thresholds (other than their general existence)
will almost always be wrong, and this may thus be seen as reducing the
credibility of scenario theory. Thus there may be a tendency for most
scenarios, especially those developed by groups, to understate their frequency
and severity. Thresholds are also problematic for quantitative modelers, who
can still rarely factor thresholds into their models. Imagine, for example, the
political difficulty of introducing an equation that specifies a
population-reducing calamity such as a civil war once population density,
poverty, and inequality exceed thresholds.
But, excluding such factors can produce implausibly optimistic scenarios. For
example, the United Nations Population Division has long provided forecasts of
the global population based only on demographic factors such as birthrates and
average life expectancy. The possibility of large-scale war is entirely absent
from consideration, and has led to absurdly high projections of maximum global
population. Although more recent UN population projections have been lowered in
response to the scale of the HIV epidemic, their projections continue to
assume, implausibly, an absence of other adverse threshold events.
In other cases, the inability to factor in positive social thresholds may lead
to excessively pessimistic scenarios. One such pessimistic scenario posits the
almost complete loss of civil society, especially in developing countries, thus
leading to ‘‘
barbarisation’’.
Countering forces are likely to sequester such outbreaks, though with local
spread, for example to Syria and Iraq, Congo and South Sudan... but not yet to
Hawaii and Edinburgh.
Conclusion
Most scenario framers claim their visions are equally plausible, actually they
are equally implausible. Exaggerating existing tendencies to reveal clearly
distinct futures is makes such futures unlikely; a blend of various scenarios
is far more likely, but more messy and harder to sell. Most scenarios are
caricatures that will not occur on a global scale. Most scenarios are biased
toward optimism and the privileging of Western values, and understate the risk
of adverse social and environmental thresholds. Despite their limitations,
scenarios can still be of value. The imagination of alternative futures can
provide insight into policy formulation. The visualisation of adverse
consequences may influence preventive policies.
Desirable scenarios may inspire
decision makers to work constructively.
Governments, corporations, and defense organizations will continue to explore
diverse scenarios. Adding social, environmental, climatic, ecologic, and health
aspects to the scenario literature can only help. More place is warranted for desirable
scenarios. Scenario workers could then work backward from this imagined future
to the present to see how it might be achieved. The wide involvement of civil
society in the process of imagining such a future (though not one that is
utopian) could be useful.
Global social affairs are enormous juggernaut, beyond control and operating in
a competitive global market on a planet with limited resources and a human
population that may be beginning to realize its collective footprint and,
perhaps, its collective responsibility. Although ideally we will look before we
leap, ‘‘he who hesitates is lost’’ may reflect the competitive pressure that
most people work with. These competitive forces constrain the power of decision
makers to influence the future.
The global environmental system has tremendous inertial and self-organizational
properties. Although humans have long influenced the global environment, it is
hubristic to think geo-engineering or other strategies will radically and
beneficially alter this environment within a few generations. At best, our
influence will probably be painfully limited, although a small contribution
could still prove very valuable, given that we do not yet know the full
biosocial capacity of the planet.
Workers in health, ecology, and other fields related to sustainability can
collectively make a crucial contribution. This is to challenge the view that
limits are neither real nor close. The excessively optimistic counterview,
found especially in some economic and demographic literature, has been
characterized as one that ‘‘lays stress on new ideas as a source of progress,
supposing that the growth of ideas is capable of circumventing any constraint
the natural-resource base may impose on the ability of economies to grow
indefinitely’’ (Dasgupta, 2000).
This counterview is powerful in the worldview of many currently influential
people. Taken to extremes, it is a kind of magical thinking. Alan Greenspan
proclaimed faith in the capacity of the market to generate solutions to the
current high cost of oil. I too have some faith in the capacity of society to
solve its problems, as does
Dasgupta.
However, left to the market alone, such solutions are likely to be at a high
social cost.
Technology is not the only crucial element for the future, including for
health. The quality of our institutions, culture, aspirations, rules, norms,
and resource distribution is of at least equal importance. Science needs to
contribute to both. Peering into the fog, it is still possible to discern a future
better than the present, but it will take much hard work, the change of some
fundamental values, and, probably, a good measure of luck.
Dasgupta P (2000)
Population
and resources: an exploration of reproductive and environmental externalities.
