Predicting the Future in Science, Economics, and Politics
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Predicting the Future in Science, Economics, and Politics

Edited by Frank Whelon Wayman, Paul R. Williamson, Bruce Bueno de Mesquita and Solomon Polachek

It is a puzzle that while academic research has increased in specialization, the important and complex problems facing humans urgently require a synthesis of understanding. This unique collaboration attempts to address such a problem by bringing together a host of prominent scholars from across the sciences to offer new insights into predicting the future. They demonstrate that long-term trends and short-term incentives need to be understood in order to adopt effective policies, or even to comprehend where we currently stand and the sort of future that awaits us.
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Chapter 11: Forecasting the evolution of cultural collisions using annealing-nucleation models

Myron S. Karasik


The “anvil” of history lies at intersectional boundaries of cultures. Australia, cut off from the human family for 40 000 years, demonstrates clearly the innate conservatism of successful human traditions. On the other hand, during the same period of time, the permeable boundaries of human cultures, particularly in Eurasia (and most recently, the Americas), have been the wellsprings of our evolutionary history in recent times. They still remain the driving force of future evolution of human socio-political and economic development. Using the concept of annealing-nucleation from the physics of materials, we can predict global evolutionary behaviors over relatively short periods. The macroscopic behavior of materials, representing the sums of many individual components, can be modeled through a relative handful of boundary value measures representing the difference between dissonance experienced by the components, action proclivities, and degree of credibility of communications that are analogous to temperature, field strength, spin orientation, and so on Just as modern weather forecasting has become a more reliable tool through use of similar models and computationally efficient processing of large numbers of instrumented data points through “grouping” techniques, so the ability to forecast major socio-political and economic “storms” could be developed based on a few core principles.

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