The checkered history of predicting the future-e.g., "Man will never fly"-has dissuaded policymakers from considering the long-term effects of decisions. New analytic methods, enabled by modern computers, transform our ability to reason about the future. The authors here demonstrate a quantitative approach to long-term policy analysis (LTPA). Robust methods enable decisionmakers to examine a vast range of futures and design adaptive strategies to be robust across them. Using sustainable development as an example, the authors discuss how these methods apply to LTPA and a wide range of decisionmaking under conditions of deep uncertainty.
Robert J. Lempert (Ph.D., Applied Physics, Harvard University) is a senior physical scientist at RAND. Dr. Lempert's recent work has focused on science and technology policy.
Steven W. Popper (Ph.D., Economics, UC Berkeley) is a senior economist in RAND's International Policy Department and serves as Associate Director of the Science and Technology Policy Institute.
Steven C. Bankes (Ph.D., Computer Science, University of Colorado) is a senior computer scientist at RAND. Dr. Bankes is the originator of the computational research methodologies known as "exploratory modeling," which provide a basis for studying complex, adaptive, and incompletely understood systems through computational experiments.