Tài liệu Geological and Geotechnical Engineering in the New Millennium: Opportunities for Research

Committee on Forecasting Future Disruptive Technologies

Division on Engineering and Physical Sciences

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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

vii

Technological innovations are key causal agents of surprise and disruption. These innovations, and the disrup￾tion 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 Engi￾neering (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 character￾istics 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 contribu￾tions 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

Preface

viii

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.

ix

SUMMARY 1

1 NEED FOR PERSISTENT LONG-TERM FORECASTING OF DISRUPTIVE TECHNOLOGIES 8

Rationale for Creating a New Forecasting System, 10

How a Disruptive Technology Differs From an Emerging Technology, 11

Disruptive Versus Emerging Technologies, 11

What Is a Disruptive Technology?, 11

Forecasting Disruptive Technologies, 13

Useful Forecasts, 15

Tools as Signposts, 15

Tipping Points as Signposts, 15

Report Structure, 16

References, 16

Published, 16

Unpublished, 16

2 EXISTING TECHNOLOGY FORECASTING METHODOLOGIES 17

Introduction, 17

Technology Forecasting Defined, 17

History, 17

Defining and Measuring Success in Technology Forecasting, 18

Technology Forecasting Methodologies, 20

Judgmental or Intuitive Methods, 20

Extrapolation and Trend Analysis, 21

Models, 24

Scenarios and Simulations, 27

Other Modern Forecasting Techniques, 28

Time Frame for Technology Forecasts, 30

Conclusion, 31

References, 31

Contents

CONTENTS

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

CONTENTS xi

Enablers, Inhibitors, and Precursors of Disruption, 76

Signal Detection Methods, 77

Exception and Anomaly Processing Tools, 79

Outputs and Analysis, 82

Signal Evaluation and Escalation, 82

Visualization, 82

Postprocessing and System Management Considerations, 87

Review and Reassess, 87

System Management, 88

Resource Allocation and Reporting, 90

References, 90

Published, 90

Unpublished, 91

6 EVALUATING EXISTING PERSISTENT FORECASTING SYSTEMS 92

Introduction, 92

Delta Scan, 92

Strengths and Weaknesses, 93

TechCast, 95

Strengths and Weaknesses, 95

X-2 (Signtific), 98

Strengths and Weaknesses, 101

Evaluation of Forecasting Platforms, 102

References, Unpublished, 104

7 CONCLUSION 105

Benchmarking a Persistent Forecasting System, 105

Steps to Build a Persistent Forecasting System for Disruptive Technologies, 105

Conclusion, 109

APPENDIXES

A Biographical Sketches of Committee Members 113

B Meetings and Speakers 117