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Research Question

  1. What should DARPA's priorities be for investment in social-behavioral modeling so that such modeling can more effectively aid in understanding and addressing national problems?

This report summarizes priority challenges for social-behavioral modeling, which has not yet begun to reach its full potential. Some of the obstacles reflect inherent challenges: Social systems are complex adaptive systems; they often pose "wicked problems," and even the structure of social systems shows emergent behavior. Other obstacles reflect disciplinary norms and practices, mindsets, and numerous scientific and methodological challenges. We discuss challenges in six groups:

  1. Improving the research cycle by tightening links among theory, modeling, and experimentation.
  2. Seeking more unifying and coherent theories while retaining alternative perspectives and confronting multidimensional uncertainty.
  3. Invigorating experimentation with modern data sources and emphasis on theory-observation iteration.
  4. Modernizing ways to use social-behavioral models for analysis to aid decisionmaking, in particular by drawing on lessons learned from other domains about using models to assist planning under deep uncertainty.
  5. Challenging theorists and technologists to provide related methods and tools, since those that exist now are inadequate and often counterproductive.
  6. Nurturing the rest of the ecology needed (notably infrastructure, governance, and culture), and doing so in a way that adheres to the highest standards with regard to ethics, privacy, and responsible use of model-based analysis to inform policy decisions that may have profound effects.

Key Findings

Social-Behavioral (SB) Modeling Is Famously Hard but Has Great Potential

  • For SB modeling to achieve its potential, great advances are needed in understanding the states of complex adaptive systems and recognizing when interventions are and are not controllable.
  • Many SB issues are so-called wicked problems with no a priori solutions. If they are found at all, solutions must emerge from human interactions.
  • The very nature of social systems is structurally dynamic, so structure changes may emerge after interactions and events, which complicates modeling.
  • Obstacles to progress include disciplinary norms, mindsets, and some discrete scientific challenges, including out-of-kilter relationships among theory development, empiricism, and computational exploration.
  • Another obstacle is the need to rethink how social-behavioral models can be best used to aid decisionmaking. Given inherent uncertainties, emphasis should change from efforts to predict outcomes toward efforts to anticipate and understand possible outcomes and ways to improve the likelihood of desirable outcomes (perhaps with adaptations). This will include understanding when interventions are likely to be uncontrollable and perhaps counterproductive.

Recommendations

Investment priorities should be in six groups:

  • Improving the research cycle by tightening links among theory, modeling, and experimentation
  • Seeking more unifying and coherent theories while retaining alternative perspectives and confronting multidimensional uncertainty
  • Invigorating experimentation with modern data sources and emphasis on theory-observation iteration
  • Modernizing ways to use social-behavioral models for analysis to aid decisionmaking, in particular by drawing on lessons learned from other domains about using models to assist planning under deep uncertainty
  • Challenging theorists and technologists to provide related methods and tools, since existing ones are inadequate and often counterproductive
  • Nurturing the rest of the ecology needed (notably infrastructure, governance, and culture), and doing so in a way that adheres to the highest standards with regard to ethics, privacy, and responsible use of model-based analysis to inform policy decisions that may have profound effects

A mechanism for addressing the priorities should be able to identify a small number of grand challenges and, for each, to organize multiyear research using virtual social-behavioral modeling laboratories to stimulate cross-cutting, interdisciplinary, iconoclastic research addressing challenges in all of the six groups.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    Difficulties, Challenges, and a Broad Strategy for Next Steps

  • Chapter Three

    Broad Strategy for Next Steps

  • Chapter Four

    Tightening the Theory-Modeling-Experimentation Research Cycle

  • Chapter Five

    Theory and Its Modeling

  • Chapter Six

    Experimentation

  • Chapter Seven

    Modernizing Model-Based Decision Aiding

  • Chapter Eight

    Methods and Technology

  • Chapter Nine

    Infrastructure, Culture, and Governance

  • Appendix A

    Social and Behavioral Modeling Laboratories

  • Appendix B

    Definitions

  • Appendix C

    Validation

  • Appendix D

    Participants in Workshops

  • Appendix E

    eeee

The research in this report was sponsored by Dr. Jonathan Pfautz, a program manager in DARPA's Information Innovation Office (I20) and conducted within the International Security and Defense Policy Center and Acquisition and Technology Policy Center of the RAND National Defense Research Institute, a federally funded research and development center sponsored by the Office of the Secretary of Defense, the Joint Staff, the Unified Combatant Commands, the Navy, the Marine Corps, the defense agencies, and the defense intelligence community.

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