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Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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PERSISTENT FORECASTING OF DISRUPTIVE TECHNOLOGIES

Committee on Forecasting Future Disruptive Technologies

Division on Engineering and Physical Sciences

NATIONAL RESEARCH COUNCIL OF THE NATIONAL ACADEMIES

THE NATIONAL ACADEMIES PRESS

Washington, D.C.
www.nap.edu

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
×

THE NATIONAL ACADEMIES PRESS

500 Fifth Street, N.W. Washington, DC 20001

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance.

This is a report of work supported by contract No. HHM40205D0011 between the Defense Intelligence Agency and the National Academy of Sciences. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the organizations or agencies that provided support for the project.

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Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
×

THE NATIONAL ACADEMIES

Advisers to the Nation on Science, Engineering, and Medicine


The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Ralph J. Cicerone is president of the National Academy of Sciences.


The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. Dr. Charles M. Vest is president of the National Academy of Engineering.


The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Harvey V. Fineberg is president of the Institute of Medicine.


The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Ralph J. Cicerone and Dr. Charles M. Vest are chair and vice chair, respectively, of the National Research Council.


www.national-academies.org

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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COMMITTEE ON FORECASTING FUTURE DISRUPTIVE TECHNOLOGIES

GILMAN G. LOUIE, Chair,

Alsop Louie Partners, San Francisco

PRITHWISH BASU,

BBN Technologies, Cambridge, Massachusetts

HARRY BLOUNT,

Blount Ventures, Hillsborough, California

RUTH A. DAVID,

ANSER, Arlington, Virginia

STEPHEN DREW,

Drew Solutions, Inc., Summit, New Jersey

MICHELE GELFAND,

University of Maryland, College Park

JENNIE S. HWANG,

H-Technologies Group, Cleveland, Ohio

ANTHONY K. HYDER,

University of Notre Dame, Indiana

FRED LYBRAND,

Elmarco, Inc., Chapel Hill, North Carolina

PAUL SAFFO,

Saffo.com, Burlingame, California

PETER SCHWARTZ,

Global Business Network, San Francisco

NATHAN SIEGEL,

Sandia National Laboratories, Albuquerque, New Mexico

ALFONSO VELOSA, III,

Gartner, Inc., Tuscon, Arizona

Staff

MICHAEL A. CLARKE, Lead DEPS Board Director

DANIEL E.J. TALMAGE, JR., Study Director

LISA COCKRELL, Mirzayan Policy Fellow, Senior Program Associate (until 8/10/2009)

ERIN FITZGERALD, Mirzayan Policy Fellow, Senior Program Associate (until 8/14/2009)

KAMARA BROWN, Research Associate

SARAH CAPOTE, Research Associate

SHANNON THOMAS, Program Associate

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Preface

Technological innovations are key causal agents of surprise and disruption. These innovations, and the disruption they produce, have the potential to affect people and societies and therefore government policy, especially policy related to national security. Because the innovations can come from many sectors, they are difficult to predict and prepare for. The purpose of predicting technology is to minimize or eliminate this surprise. To aid in the development of forecasting methodologies and strategies, the Committee on Forecasting Future Disruptive Technologies of the National Research Council (NRC) was funded by the Director, Defense Research and Engineering (DDR&E) and the Defense Intelligence Agency’s (DIA’s) Defense Warning Office (DWO) to provide an analysis of disruptive technologies.

This is the first of two planned reports. In it, the committee describes disruptive technology, analyzes existing forecasting strategies, and discusses the generation of technology forecasts, specifically the design and characteristics of a long-term forecasting platform. In the second report, the committee will develop a hybrid forecasting method tailored to the needs of the sponsors.

As chairman, I wish to express our appreciation to the members of this committee for their earnest contributions to the generation of this first report. The members are grateful for the active participation of many members of the technology community, as well as to the sponsors for their support. The committee would also like to express sincere appreciation for the support and assistance of the NRC staff, including Michael Clarke, Daniel Talmage, Lisa Cockrell, Erin Fitzgerald, Kamara Brown, Sarah Capote, Carter Ford, and Shannon Thomas.


Gilman G. Louie, Chair

Committee on Forecasting Future Disruptive Technologies

Page viii Cite
Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Acknowledgment of Reviewers

This report has been reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise, in accordance with procedures approved by the National Research Council’s Report Review Committee. The purpose of this independent review is to provide candid and critical comments that will assist the institution in making its published report as sound as possible and to ensure that the report meets institutional standards for objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We wish to thank the following individuals for their review of this report:

Peter M. Banks, NAE, Astrolabe Ventures,

Andrew Brown, Jr., NAE, Delphi Corporation,

Natalie W. Crawford, NAE, RAND Corporation,

Thom J. Hodgson, NAE, North Carolina State University,

Anita K. Jones, NAE, University of Virginia,

Julie J. C. H. Ryan, George Washington University,

Kenneth W. Wachter, NAS, University of California, Berkeley, and

Ruoyi Zhou, IBM Almaden Research Center.

Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations nor did they see the final draft of the report before its release. The review of this report was overseen by Maxine Savitz (NAE), Honeywell (retired). Appointed by the NRC, she was responsible for making certain that an independent examination of this report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring committee and the institution.

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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3

 

THE NATURE OF DISRUPTIVE TECHNOLOGIES

 

33

   

 The Changing Global Landscape,

 

33

   

 Effects of the Education of Future Generations,

 

34

   

 Attributes of Disruptive Technologies,

 

34

   

 Categorizing Disruptive Technologies,

 

37

   

 Disrupter, Disrupted, and Survivorship,

 

37

   

 Life Cycle,

 

38

   

 Assessing Disruptive Potential,

 

40

   

 Technology Push and Market Pull,

 

41

   

 Investment Factors,

 

42

   

 Cost as a Barrier to Disruption,

 

43

   

 Regional Needs and Influences,

 

43

   

 Social Factors,

 

44

   

 Demographic Factors,

 

44

   

 Geopolitical and Cultural Influences,

 

45

   

 Practical Knowledge and Entrepreneurship,

 

45

   

 Crossover Potential,

 

45

   

 Conclusion,

 

46

   

 References,

 

47

4

 

REDUCING FORECASTING IGNORANCE AND BIAS

 

48

   

 Introduction,

 

48

   

 Ignorance,

 

48

   

 Closed Ignorance,

 

49

   

 Open Ignorance,

 

49

   

 Bias,

 

51

   

 Age Bias,

 

52

   

 Mitigating Age Bias,

 

52

   

 Cultural Bias,

 

53

   

 Mitigating Cultural Bias,

 

54

   

 Reducing Linguistic Bias,

 

54

   

 Conclusion,

 

55

   

 References,

 

55

5

 

IDEAL ATTRIBUTES OF A DISRUPTIVE TECHNOLOGY FORECASTING SYSTEM

 

57

   

 Tenets of an Ideal Persistent Forecasting System,

 

57

   

 Persistence,

 

58

   

 Openness and Breadth,

 

58

   

 Proactive and Ongoing Bias Mitigation,

 

61

   

 Robust and Dynamic Structure,

 

61

   

 Provisions for Historical Comparisons,

 

61

   

 Ease of Use,

 

61

   

 Information Collection,

 

62

   

 Considerations for Data Collection,

 

62

   

 Key Characteristics of Information Sources,

 

64

   

 Potential Sources of Information,

 

65

   

 Cross-Cultural Data Collection,

 

69

   

 Data Preprocessing,

 

70

   

 Information Processing,

 

72

   

 Trends to Track,

 

73

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Acronyms and Abbreviations

ARG alternate reality games

BOINC Berkeley Open Infrastructure for Network Computing

CAS complex adaptive system

DARPA Defense Advanced Research Projects Agency

DDR&E Director, Defense Research and Engineering

DNA deoxyribonucleic acid

DoD Department of Defense

DWO Defense Warning Office

EC2 elastic compute cloud

ETL extract, transform, and load

GDP gross domestic product

GPS Global Positioning System

GUI graphical user interface

HD high definition

IC intelligence community

IED improvised explosive device

IEEE Institute of Electrical and Electronics Engineers

IFTF Institute for the Future

MCF meta content framework

MEMS microelectromechanical systems

MMORPG massive multiplayer online role-playing game

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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NaCTeM National Center for Text Mining

NASA National Aeronautics and Space Administration

NATO North Atlantic Treaty Organization

NGO nongovernmental organization

NORA Nonobvious Relationship Awareness

NRC National Research Council

NSF National Science Foundation

PC personal computer

PCR polymerase chain reaction

QDR quadrennial defense review

R&D research and development

RDB relational database

RDF resource description framework

S3 Simple Storage Service

SAS Statistical Analysis Software

SIMS School of Information Management and Systems, University of California at Berkeley

SMT simultaneous multithreading

TIGER Technology Insight–Gauge, Evaluate, and Review

T-REX The RDF Extractor, a text mining tool developed at the University of Maryland

TRIZ Rus: Teoriya Resheniya Izobretatelskikh Zadatch (“inventor’s problem-solving theory”)

U.S. United States

WWII World War Two

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Glossary

Backcasting Explores a future scenario for potential paths that could lead from the present to the forecast future.

Breakthrough Discovery or technology that changes a fundamental understanding of nature or makes possible something that previously seemed impossible (or improbable).

Catalyst Technology that alters the rate of change of a technical development or alters the rate of improvement of one or more technologies.

Chaos theory Characterizes deterministic randomness, which indeed exists in the initial stages of technology phase transition.

Delphi method Structured approach to eliciting forecasts from groups of experts, with an emphasis on producing an informed consensus view of the most probable future.

Disruption Event that significantly changes or interrupts movement or a process, trend, market, or social direction (Source: Dictionary.com).

Disruptive technology Innovative technology that triggers sudden and unexpected effects. The term was first coined by Bower and Christensen in 1995 to refer to a type of technology that brings about a sudden change to established technologies and markets (Bower and Christensen, 1995). Because these technologies are characteristically hard to predict and occur infrequently, they are difficult to identify or foresee.

Enhancer Technology that modifies existing technologies, allowing a measure of interest in the technologies to cross a critical threshold or tipping point.

Enabler Technology that makes possible one or more new technologies, processes, or applications.

Extrapolation Use of techniques such as trend analyses and learning curves to generate forecasts.

Forecasting bias Incompleteness in the data sets or methodologies used in a forecasting system (meaning in this report).

Genius forecast Forecast by a single expert who is asked to generate a prediction based on his or her intuition.

Suggested Citation:"Front Matter." National Research Council. 2010. Persistent Forecasting of Disruptive Technologies. Washington, DC: The National Academies Press. doi: 10.17226/12557.
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Ignorance Lack of knowledge or information. Ignorance contributes to bias in a forecast, which in turn can cause surprise.

Individual bias Prejudice held by a human being.

Influence diagram Compact graphical or mathematical representation of the decision-making process.

Intuitive view Opinion that the future is too complex to be adequately forecast using statistical techniques but should instead rely primarily on the opinions or judgment of experts.

Long-term forecasts Forecasts of the deep future (10 or more years from the present).

Measurement of interest Key characteristic that can be monitored to anticipate the development of disruptive technologies and applications.

Medium-term forecasts Forecasts of the intermediate future (typically 5 to 10 years from the present).

Morpher Technology that creates one or more new technologies when combined with another technology.

Persistent forecast Forecast that is continually improved as new methodologies, techniques, or data become available.

Scenario Tool for understanding the complex interaction of a variety of forces that can influence future events (meaning in this report).

Short-term forecasts Forecasts that focus on the near future (5 years or less from the present).

Signal Piece of data, a sign, or an event that is relevant to the identification of a potentially disruptive technology.

Signpost Recognized and actionable potential future event that could indicate an upcoming disruption.

Superseder New, superior technology that obviates an existing technology by replacing it.

Surprise Being taken unawares by some unexpected event.1

Techno cluster Geographic concentration of interconnected science- and high-tech-oriented businesses, suppliers, and associated institutions.

Technological innovation Successful execution of a fundamentally new technology or key development in the performance of an existing product or service.

Technology forecasting Prediction of the invention, timing, characteristics, dimensions, performance, or rate of diffusion of a machine, material, technique, or process serving some useful purpose.2

Technology forecasting system Technologies, people, and processes assembled to minimize surprise triggered by emerging or disruptive technologies, in order to support decision making.

Tipping point Time at which the momentum for change becomes unstoppable (Walsh, 2007).

Trend extrapolation Forecasting method in which data sets are analyzed to identify trends that can provide predictive capability.

TRIZ A forecasting system that uses a set of rules, termed “laws of technological evolution,” that describe how technologies change throughout their lifetimes because of innovation and other factors, resulting in the development of new products, applications, and technologies.

1

Adapted from the Oxford English Dictionary, available at http://www.askoxford.com/concise_oed/ignorance?view=uk. Last accessed August 25, 2009.

2

The committee modified the definition of Martino (1969) to reflect the evolving practice of technology forecasting; accordingly, it included the rate of diffusion, which is a critical element in modern forecasting, and defined technology to include materials.

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Technological innovations are key causal agents of surprise and disruption. In the recent past, the United States military has encountered unexpected challenges in the battlefield due in part to the adversary's incorporation of technologies not traditionally associated with weaponry. Recognizing the need to broaden the scope of current technology forecasting efforts, the Office of the Director, Defense Research and Engineering (DDR&E) and the Defense Intelligence Agency (DIA) tasked the Committee for Forecasting Future Disruptive Technologies with providing guidance and insight on how to build a persistent forecasting system to predict, analyze, and reduce the impact of the most dramatically disruptive technologies. The first of two reports, this volume analyzes existing forecasting methods and processes. It then outlines the necessary characteristics of a comprehensive forecasting system that integrates data from diverse sources to identify potentially game-changing technological innovations and facilitates informed decision making by policymakers.

The committee's goal was to help the reader understand current forecasting methodologies, the nature of disruptive technologies and the characteristics of a persistent forecasting system for disruptive technology. Persistent Forecasting of Disruptive Technologies is a useful text for the Department of Defense, Homeland Security, the Intelligence community and other defense agencies across the nation.

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