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Persistent Forecasting of Disruptive Technologies
low enough to cause a significant change in the pattern of consumption, perhaps even mass substitution, or to the moment something unique becomes common.2
This report is the first of two on the topic requested by the sponsors. In this first report, the committee discusses how technology forecasts are made, assesses the various systems investigated by the committee, and identifies the attributes of a persistent, long-term disruptive technology forecasting system. Chapter 2 of this report outlines the history of technology forecasting and describes current forecasting methodologies and approaches; it also helps to further define and provide metrics for a successful forecast. Chapter 3 describes the nature of disruptive technologies, suggests sectors where disruptive technology is likely to take place, and identifies disciplines of interest for future study. Chapter 4 discusses bias and other factors that can affect the validity of a forecast. Chapter 5 proposes an approach to developing an ideal persistent disruptive technology forecast. In Chapter 6, existing forecasting systems (including those specified in this report’s statement of task) are benchmarked against the ideal system. Finally, the conclusion (Chapter 7) suggests a process to build a persistent forecasting system and lists its potential applications.
In the second report, the committee plans to summarize the results of a workshop that will have assembled experts on forecasting, system architecture, and visualization. The experts will have been asked to envision a system that meets the sponsor’s requirements while incorporating the suggestions in this report.
Gladwell, Malcolm. 2000. The Tipping Point: How Little Things Can Make a Big Difference. London: Little, Brown and Company.
NRC (National Research Council). 2005. Avoiding Surprise in an Era of Global Technology Advances. Washington, D.C.: The National Academies Press. Available at http://www.nap.edu/catalog.php?record_id=11286. Last accessed November 5, 2008.
Strong, R., J. Ryan, D. McDavid, Y. Leung, R. Zhou, E. Strauss, J. Bosma, T. Sabbadini, D. Jarvis, S. Sachs, P. Bishop, and C. Clark. 2007. A new way to plan for the future. Proceedings of the 40th Hawaii International Conference on Systems Science.