G2TT
来源类型Report
规范类型报告
DOIhttps://doi.org/10.7249/RR-A701-1
来源IDRR-A701-1
A Structured Elicitation Approach to Identify Technology-Based Challenges: With Application to Inform Force Planning for Technological Surprise
Lauren A. Mayer; Jon Schmid; Sydney Litterer; Marjory S. Blumenthal
发表日期2021-10-14
出版年2021
语种英语
结论
  • A structured expert elicitation approach permits the transparent and reliable identification of themes and criteria for evaluating potential technology-based challenges to the Joint Force.
  • RAND experts nominated a total of 40 technology-initiated challenges, which were consolidated into 20 challenges for evaluation. These challenges varied in terms of technologies, adversaries, and external factors, with potentially greater representation from challenges with technologies involving autonomy, machine learning or analysis of "big data," the space domain, and a China adversary.
  • Experts derived several broad criteria for evaluating whether a challenge would be radically altering for DoD: barriers to DoD identification and prevention, other barriers (e.g., feasibility of technology development or adaptation), mitigation difficulty, impact on operations, impact on national security, urgency of investment, and national defense priority.
  • Experts' evaluation of the 20 challenges highlighted three clusters. The top cluster contains nine challenges that experts believed need urgent S&T investments, should be a major national defense priority, might have impacts with severe consequences, and overall were higher risk to DoD and the United States. The middle cluster contains seven challenges that experts believed might have impacts with severe consequences but that did not significantly need urgent S&T investment or need to be a major defense national priority. The bottom cluster contains four challenges that experts did not believe had significance across the dimensions the authors measured.
摘要

This report describes an approach developed to elicit from experts ideas for technology-based challenges that the U.S. Joint Force could confront in the year 2040, as well as results from employing this approach with internal RAND Corporation experts. The approach begins with conducting and qualitatively analyzing a set of exploratory interviews with experts, which in turn informs an open-ended survey to nominate challenges and a close-ended survey to evaluate those challenges.

,

Applying this approach with RAND experts generated 20 challenges. Evaluation of those challenges produced three general clusters: a top cluster with nine challenges that experts believed need urgent science and technology (S&T) investments, should be a major national defense priority, might have impacts with severe consequences, and overall were higher risk to the U.S. Department of Defense (DoD) and the United States; a middle cluster with seven challenges that experts believed might have impacts with severe consequences but did not significantly need urgent S&T investment or need to be a major defense national priority; and a bottom cluster with four challenges that experts did not believe had significance across the dimensions the authors measured.

目录
  • Chapter One

    Introduction

  • Chapter Two

    Exploratory Interviews

  • Chapter Three

    Challenge Nominations

  • Chapter Four

    Challenge Evaluation

  • Chapter Five

    Discussion

  • Appendix A

    Exploratory Interview Materials

  • Appendix B

    Challenge Nomination and Evaluation Materials

  • Appendix C

    Selected Nominated Challenges

  • Appendix D

    Descriptive Statistics of Challenge Evaluation Results

主题Artificial Intelligence ; Decisionmaking ; Emerging Technologies ; Military Technology ; Survey Research Methodology
URLhttps://www.rand.org/pubs/research_reports/RRA701-1.html
来源智库RAND Corporation (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/524593
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Lauren A. Mayer,Jon Schmid,Sydney Litterer,et al. A Structured Elicitation Approach to Identify Technology-Based Challenges: With Application to Inform Force Planning for Technological Surprise. 2021.
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