G2TT
来源类型Report
规范类型报告
DOIhttps://doi.org/10.7249/RRA161-1
来源IDRR-A161-1
Influencing Adversary States: Quelling Perfect Storms
Paul K. Davis; Angela O'Mahony; Christian Curriden; Jonathan Lamb
发表日期2021-02-16
出版年2021
语种英语
结论

Deterrent efforts should be seen as elements of much broader influence strategies

  • Deterring adversaries by threat of punishment is often ineffective by itself. Better influence strategies include, e.g., being able to thwart aggression, reassurances to reduce the adversary's fears, incentives, conditional reciprocity, relationship-building, and both direct and indirect forms of dissuasion.
  • Influence strategies depend on affecting Red's thinking, not just displaying strength.
  • Considering alternative models of Red can improve strategy and its adaptiveness.

Understanding how an adversary reasons and perceives U.S. actions will help decisionmakers develop effective influence strategies

  • Influence strategies should be guided by thinking Red, but this is notoriously difficult. It is very helpful to identify alternative ways that Red may be thinking, to take these alternatives seriously, and to pursue an adaptive strategy likely to be effective for all of them.
  • A decision-aiding doctrine for doing so would be quite different from the common approach of focusing on a best-estimate image of Red, which often proves wrong.
  • A method called uncertainty sensitive cognitive modeling could help with effective thinking-Red and could suggest elements of influence strategy.
  • Such modeling could include gaming, other human exercises, and qualitative modeling to create a coherent depiction of insights.
  • Prototype experiments suggest that such a process is feasible and could be insightful. The approach suggested is ready for more-realistic testing in a variety of context.
摘要

In this report, the authors describe an experimental "thinking-Red" approach to analysis, wargaming, and other exercises that may help inform strategies to avoid aggression or escalation in a crisis. This thinking-Red approach focuses on how to influence an adversary's reasoning in ways that the decisionmaker regards as favorable. It does so with alternative models of the adversary. An influence strategy might involve a mix of deterrence by threat of punishment, deterrence by denial, dissuasion by many means, reassurances, and incentives. Deterrent threats alone will seldom constitute effective strategy and, depending on the adversary's motivations and perceptions, could even be counterproductive. A successful strategy will also often require artful orchestration of political, military, and economic instruments of power.

,

The approach can be applied to (1) diverse potential adversaries, (2) both direct and gray-zone conflicts, and (3) different levels of crisis, conflict or competition. Each of the three applications will require an in-depth study of substantive issues and refining methods and tools, but the potential scope of applications is wide.

目录
  • Chapter One

    Introduction

  • Chapter Two

    Lessons from History and Psychology

  • Chapter Three

    Cognitive Modeling and Thinking-Red Exercises

  • Chapter Four

    Illustration: Hypothetical Crisis with China

  • Chapter Five

    Conclusions

  • Appendix A

    Mathematics of Thresholded Linear Weighted Sums

  • Appendix B

    Computational Version of Factor Tree Model

  • Appendix C

    Bayesian Updating of Red's Blue: Simple Artificial Intelligence

  • Appendix D

    Input Data for Model

  • Appendix E

    Simplifying Probabilistic Calculations

主题Decisionmaking ; Discrete Choice Modeling ; Exploratory Modeling ; Game Theory ; Military Strategy ; Wargaming
URLhttps://www.rand.org/pubs/research_reports/RRA161-1.html
来源智库RAND Corporation (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/524370
推荐引用方式
GB/T 7714
Paul K. Davis,Angela O'Mahony,Christian Curriden,et al. Influencing Adversary States: Quelling Perfect Storms. 2021.
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