Table of Contents

Predicting the Future in Science, Economics, and Politics

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.

Chapter 2: Organizing diverse contributions to global forecasting

Paul R. Williamson

Subjects: economics and finance, game theory, international economics, politics and public policy, international politics, international relations, public policy

Extract

The elements that may contribute to computational global societal– environmental modeling and forecasting – herein simply “modeling’’ or “global modeling” where clarity permits – take the form of contributions from greatly diverse sources. Some of these (somewhat skewed in the direction of social inquiries) are speculatively indicated by the categories in Table 2.1. This chapter offers a set of themes, set forth below, for connecting such elements. This particular set of ideas is not meant to be unique; there may be, no doubt are, other ways of doing the connecting; nor will the present discussion do more than briefly treat the themes to be considered. The organizing principle that I propose is that the various elements may be described and compared in terms of the themes. This suggested organization is, thus, a very loose one. It is not a substitute for the ideal of a consistent, coherent, validated, maximally compacted organization of elements, but my suggestion is that the indicated comparative descriptions may help move global modeling in the direction of that ideal. The rationale for these particular themes is that to do successful global modeling one needs to look, anew, at modern physical science as both exemplar and basis of global knowledge.

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