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Persistent Forecasting of Disruptive Technologies
Postulating potential alternative futures, and
Supporting decision making by increasing the lead time for awareness.
The Office of the Director of Defense Research and Engineering (DDR&E) and the Defense Intelligence Agency (DIA) Defense Warning Office (DWO) asked the National Research Council (NRC) to set up a committee on forecasting future disruptive technologies to provide guidance on and insight into the development of a system that could forecast disruptive technology. The sponsor recognizes that many of the enabling disruptive technologies employed by an enemy could potentially come out of nonmilitary applications. Understanding this problem, the sponsor asked the committee to pay particular attention to ways of forecasting technical innovations that are driven by market demand and opportunities. It was agreed that the study should be unclassified and that participation in it not require security clearances. The sponsor and the committee strongly believe that if a forecasting system were to be produced that was useful in identifying technologies driven by market demand, especially global demand, then it would probably have significant value to a broad range of users beyond the Department of Defense and outside the United States. The sponsor and the committee also believe that the creation of an unclassified system is crucial to their goal of eliciting ongoing global participation. The sponsor asked the committee to consider the attributes of “persistent” forecasting systems—that is, systems that can be continually improved as new data and methodologies become available. See Box S-1 for the committee’s statement of task.
This report is the first of two requested by the sponsors. In this first report, the committee discusses how technology forecasts are made, assesses several existing forecasting systems, and identifies the attributes of a persistent disruptive forecasting system. The second report will develop forecasting options specifically tailored to needs of the sponsors.
It is important to note that the sponsor has not asked the committee to build and design a forecasting system at this time. Instead, the intent of this report is to look at existing forecasting methodologies, to discuss important attributes and metrics of a persistent system for forecasting disruptive technologies, and to examine and comment on selected existing systems for forecasting disruptive technologies.
In 2007, the sponsor contracted the development of a persistent forecasting system called X2 (the name was later changed to Signtific).3 At the time of this writing, not enough data had been generated from this system to provide a meaningful analysis of potentially disruptive technology sectors. The characteristics of X2 are analyzed in depth in Chapter 6.
CHALLENGE OF SUCH FORECASTS
All forecasting methodologies depend to some degree on the inspection of historical data. However, exclusive reliance on historical data inevitably leads to an overemphasis on evolutionary innovation and leaves the user vulnerable to surprise from rapid or nonlinear developments. In this report, a disruptive technology is an innovative technology that triggers sudden and unexpected effects. A methodology that can forecast disruptive technologies must overcome the evolutionary bias and be capable of identifying unprecedented change. A disruptive event often arrives abruptly and infrequently and is therefore particularly hard to predict using an evolutionary approach. The technology that precipitates the event may have existed for many years before it has its effect, and the effect may be cascading, nonlinear, and difficult to anticipate.
New forecasting methods must be developed if disruptive technology forecasts are to be effective. Promising areas include applications from chaos theory; artificial neural networks; influence diagrams and decision networks; advanced simulations; prediction markets; online social networks; and alternate reality games.
Signtific, originally known as the X2 project, is a forecasting system that aims to provide an innovative medium for discussing the future of science and technology. It is designed to identify the most important trends and disruptions in science and technology and their impacts on the larger society over the next 20 years. Signtific is built and run by the Institute for the Future (http://www.iftf.org/node/939).