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Stu Kaufmann: The Evolution of Future Wealth
« on: 2006-11-28 21:29:04 » |
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The Evolution of Future Wealth
source: SciAm
Technologies evolve much as species do, and that underappreciated fact
is the key to growth
By Stuart A. Kauffman
When the world changes unpredictably over the course of centuries, no
one is shocked: Who blames the Roman centurions for not foreseeing the
invention of rocket launchers? Yet monumental and surprising
transformations occur on much shorter timescales, too. Even in the
early 1980s you would have been hard-pressed to find people
confidently predicting the rise of the Internet or the fall of the
U.S.S.R. Unexpected change bedevils the business community endlessly,
despite all best efforts to anticipate and adapt to it--witness the
frequent failure of companies' five-year plans.
Economists have so far not been able to offer much help to firms
trying to be more adaptive. Although economists have been slow to
realize it, the problem is that their attempts to model economic
systems focus on those in market equilibrium or moving toward it. They
have drawn their inspiration predominantly from the work of physicists
in this respect (often with good results, of course). For instance,
the Black-Scholes model used since the 1970s to predict the volatility
of stock prices was developed by trained physicists and is related to
the thermodynamic equation that describes heat.
As economics attempts to model increasingly complicated phenomena,
however, it would do well to shift its attention from physics to
biology, because the biosphere and the living things in it represent
the most complex systems known in nature. In particular, a deeper
understanding of how species adapt and evolve may bring profound--even
revolutionary--insights into business adaptability and the engines of
economic growth.
One of the key ideas in modern evolutionary theory is that of
preadaptation. The term may sound oxymoronic but its significance is
perfectly logical: every feature of an organism, in addition to its
obvious functional characteristics, has others that could become
useful in totally novel ways under the right circumstances. The
forerunners of air-breathing lungs, for example, were swim bladders
with which fish maintained their equilibrium; as some fish began to
move onto the margins of land, those bladders acquired a new utility
as reservoirs of oxygen. Biologists say that those bladders were
preadapted to become lungs. Evolution can innovate in ways that cannot
be prestated and is nonalgorithmic by drafting and recombining
existing entities for new purposes--shifting them from their existing
function to some adjacent novel function--rather than inventing
features from scratch.
Economics should shift its attention from physics to biology
A species' suite of adaptive features defines its ecological niche
through its relations to other species. In the same way, every
economic good occupies a niche defined by its relations to
complementary and substitute goods. As the number of economic goods
increases, the number of ways in which to adaptively combine those
goods takes off exponentially, forging possibilities for all-new
niches. The autocatalytic creation of niches is thus a main driver of
economic growth.
We do not yet know what makes some systems more adaptable than others,
but research on complexity has yielded some clues. Some of my own work
on physical systems called spin glasses suggests that the level of
central control over subsidiary parts of a system is an important
consideration. Too much control freezes the system into limited
configurations; too little causes it to wander aimlessly. Only systems
that hover on the border between order and chaos exhibit the needed
general stability and capacity to explore the universe of possible
solutions to challenges.
The path to maximum prosperity will depend on finding ways to build
economic systems in which new niches will generate spontaneously and
abundantly. Such an approach to economics is indeed radical. It is
based on the emergent behavior of systems rather than on the reductive
study of them. It defies conventional mathematical treatments because
it is not prestatable and is nonalgorithmic. Not surprisingly, most
economists have so far resisted these ideas. Yet there can be little
doubt that learning to apply these lessons from biology to technology
will usher in a remarkable era of innovation and growth.
Stuart A. Kauffman is professor of biocomplexity and informatics at
the University of Calgary and external professor at the Santa Fe
Institute.
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