Part III. - IEEE International Conference on Intelligence and

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Part III. - IEEE International Conference on Intelligence and Powered By Docstoc
					Taking a Closer Look at IC Analysts




                    IC Analysts




                                      1
          Universal Similarities do Exist
                Intelligence Community Analysts

• They are far more than just casual users of information
• They work in an information rich environment where they have
  access to large quantities of heterogeneous data
• They are almost always subject matter experts within their
  assigned task areas
• They track and follow a given event, scenario, problem, or
  situation for an extended period of time
• They frequently have extensive collaboration with other analysts
• They are focused on their assigned task or mission
  and will do whatever it takes to accomplish it
• The end product that results from their
  analysis is often judged against the
  standards of:
      Timeliness         Accuracy     Usability
      Completeness       Relevance
                                                        IC Analysts 2
        Major Differences Do Exist
  (between agencies and within agencies)
• Between single source and all source analysts
  (data formats, degree of closeness to the raw
  information, accessibility to contextual information)
• Between analytical domains (counter terrorism,
  WMD, regional analysis, weapons systems, etc)
• Between types of intelligence produced (e.g. current
  intelligence, estimative intelligence, etc.)
• Experience level in the art of analysis and ability to
  understand the analytic process
• Understanding and use of analytic networks
• Customer requirements (strategic, operational,
  tactical)
• Unique individual differences
                                                           3
Intelligence Analyst’s Operational Context

            Motivation                             Objective
Prior & Tacit          Skills &           Timing           Characteristics
 Knowledge             Abilities


               Analyst                         Analysis Task




      Work                    Analyst’s              Analyst’s
   Environment                Behaviors              Colleagues



               Resources                       Organizational
                                           Policies & Procedures


    Computer             Training     Reporting               Roles &
     & SW                Material    Relationships         Responsibilities
          Guides/Handbooks                   Information Handling


                                                                              4
          Sample of an Analytic Work Flow
                                                    Collaborate with
Tasking                 Library
          Thinking                                    Colleagues
                       Research

                                                                              Completed
                                                                               Report




                                  Copy/Paste
                                   Annotate



                     Internet
                                               Compose/
                      Search
                                                 Write

                                                                         …
                                                          Compose/     Revisions
                                                            Write




Time

                                                                                          5
Fusion of Multilayer Analysis

                       Personal
                     Relationships

                     Organizational
                     Relationships

                       Technical
                    Processes/Flows

                     Transportation
                        Networks

                   Currency/Financial
                       Transfers
                Electronic Connectivity/
                   Information Flows
                                           6
              The Challenge of Time in Analysis

 • Different sources do not report simultaneously on an event.
 • Data from different sources may be near real-time or take
   years to arrive.
 • The hypothesis of today may be thrown out by new data
   arriving next week.                                 Collector
                                                       Collector 4                5 picks
Collector 1           Collectors 1,2,3
                                                     observe event-              up event
 observes             observe event
                                                      related info &             planning
   event                Collector 1      Collector
                                                         reports     Collector   material
planning &                reports        2 reports
                                                                    3 reports    in a raid
  reports
 H-n            H-1                  H+1                                          H-n
                        Event
  Event Planning                         Aftermath of the Event
                        H Hour

• Data must be visualized over time as patterns which change in
  time as updates occur
                                                                                             7
    The Challenge of Credibility in Analysis



What do we look for      What standards are we
 in a source?             held to in reporting

•   Credibility          •   Accurate
•   Reliability          •   Timely
•   Relevance            •   Actionable
•   Can be confirmed     •   Complete
                         •   Relevant

                                                 8
Where Do We Go From Here?




                            9
THE SOCIAL SCIENCES ARE, IN

FACT, THE “HARD” SCIENCES.



              GROWING ARTIFICIAL SOCIETIES
              EPSTEIN AND AXTELL

                                             10
     “NOBODY KNOWS” QUESTIONS

• WHAT IS GOING ON INSIDE THE IRAQI/SERB/NORTH
  KOREAN REGIMES?

• WHAT WOULD COLLAPSE OF THESE REGIMES
  LOOK LIKE?

• HOW STIFF A RESISTANCE WILL THE FEDAYEEN AND
OTHER SADDAAM SUPPORTERS PUT UP?

• WHAT IS GOING ON IN ANY COUNTRY, AND WHERE
IS IT GOING?

• WHAT WILL THE MIDEAST LOOK LIKE IN 2010?

• WHAT ARE THE ROOTS OF TERRORISM & HOW CAN
WE AFFECT THOSE ROOTS
  CHARACTERISTICS OF “NOBODY KNOWS”
             QUESTIONS



• COMPLEXITY
  – MANY INDEPENDENT ACTORS
  – MULTIPLE VARIABLES
  – DYNAMIC/ADAPTIVE BEHAVIOR
  – EMERGENT OUTCOMES


• HUMAN BEHAVIOR
  – INDIVIDUAL AND GROUP PROCESSES


                                      12
                  NEW APPROACHES



 TO MOVE FROM PROVIDING INTELLIGENCE
              TO PROVIDING UNDERSTANDING


              TRADITIONAL                         NEW

               ANALYSIS                        APPROACHES




INFORMATION       INTELLIGENCE     KNOWLEDGE            UNDERSTANDING


  DATA               FACTS       CONNECTIONS/               PROCESSES/
                                 RELATIONSHIPS              OUTCOMES



                                                                         13
  Potential New Approaches




• NATURAL EXPERIMENTATION

• COMPLEXITY SCIENCE

• MODELING AND SIMULATION

• WHAT ELSE?


                             14
              SOME OTHER IDEAS


• EXPERIMENT WITH AND INTEGRATE ONGOING
  EFFORTS (IC Test Nets)

• PUSH THE SCIENCE - PARTNER WITH NSF AND DARPA

• INCREASE FUNDING FOR EXPLORATORY PROGRAMS

      – SMALL GROUP MODELS

      – SOCIETAL MODELS

• SUBSIDIZE SELECT WARGAME DEVELOPERS (EXISTING
GAME ENHANCEMENTS)

• “LIBRARY” OR CROSS-REFERENCE FOR
  INTELLIGENCE RELATED SIMULATIONS
                                                  15
        ANALYSIS AND COMPLEXITY



 “THE RULES OF THE GAME: LEARN EVERYTHING,
READ EVERYTHING, INQUIRE INTO EVERYTHING…
  WHEN TWO TEXTS, OR TWO ASSERTIONS, OR
PERHAPS TWO IDEAS, ARE IN CONTRADICTION, BE
READY TO RECONCILE THEM RATHER THAN CANCEL
   ONE BY THE OTHER; REGARD THEM AS TWO
DIFFERENT FACETS, OR TWO SUCCESSIVE STAGES,
 OF THE SAME REALITY, A REALITY CONVINCINGLY
     HUMAN JUST BECAUSE IT IS COMPLEX.”
                    Marguerite Yourcenar, Memoirs of Hadrian
                                                               16
                 Non-Linear Dynamics
    of Human Behavior (NDHB) Advanced R&D Program

•   Can we achieve a better understanding of Human
    Dynamics; Individual and Small Group Behavior;
    Leadership Decision Making; Large Group Dynamics?
    Can we model it?

•   Can we use modeling approaches to influence the
    present or to forecast potential future events/activities?
    What approaches are best for which intelligence
    problems?

•   Can we use models and simulations for knowledge
    discovery?

•   Can we model across missing data?

•   Can we use models and simulations as a method for
    training analysts in hypothesis generation and
    argumentation?



                                                                 17
POSSIBLE OPERATIONAL PROBLEMS TO BE SOLVED IN
          MODELING HUMAN BEHAVIOR




•Anticipating Surprise – Asymmetric
threats & tactics
   • Avoiding technology surprise (novel ways
   of using existing technology and use of
   emerging technologies)
   • Anticipating political instability (including
   ethnic strife and state collapse)
   • Identifying plans & Intentions for threat
   operations against national US interests
        •Conventional military operations
        •Terrorism & other acts of violence
        • Information operations
        • WMD/CBNRE
   •Anticipating attacks designed to disrupt the
   economy


                                                     18
   POSSIBLE OPERATIONAL PROBLEMS TO BE SOLVED IN
          MODELING HUMAN BEHAVIOR (cont.)




•Leadership Analysis/Decision-making
(both state and non-state)
   •Formation/Transformation (regime
   change/succession/etc)
   •Coalition Dynamics
   •Influences (external/internal)
   •Plans/Intentions/Policies/Strategies

• Environmental Issues
   •Spread of diseases or C/B agents through        •Ethnic/Cultural/Religious/
   human interactions and their associated social
                                                    Societal constraints on
   impact
   • Spread of diseases through livestock and       courses of action and
   plants and impact on society (e.g. associated    decision-making (US, Allies,
   economic upheavals, starvation)                  Neutrals, Enemies)
   • Environmental disasters (either man-made or
   natural) and impact on society


                                                                               19
     Possible Applications for Modeling Human Behavior

•   Development of Threat Models (using various modeling applications)
    and analysis of results from those models

•   Fusion of intelligence from different disciplines/domains/experts with
    support from modeling and simulation

•   Integration of modeling with traditional analytic methods.
     – Training analysts to use models as part of their cognitive toolset
     – Understanding what approaches work best with different
        intelligence problems
         • Comparative case studies
         • Definitions of modeling approaches
     – Development of new analytic strategies
         •   Discovery of previously unknown data/patterns
         •   “what if”
         •   Modeling missing data and uncertainty
         •   Comparative analysis
         •   Anticipating surprise
         •   Development of new patterns/trends
         •   Comparative case studies

•   What else?                                                               20
          Possible Technical Needs for Modeling Human Behavior

                       Some Modeling Approaches

                       Individual   Small         Large
                                    Group         Group
Agent-Based
 Modeling

System Dynamics

Reaction-Diffusion

Social Network
  Analysis

Game Theory

Multiscale Analysis

Coupled Oscillators

Neural Nets

What else?
Possible Technical Needs for Modeling Human Behavior

                 Cross-cutting technologies

• Natural Language Processing

• Semi-automated and automated data loading of the model(s)

• Integration of modeling approaches

• Intuitive visualization of modeling data

• Tools to manage and analyze modeling data

• Library of models (how each model works)

• Architecture that permits sharing

• Hypothesis Generation tools

• Collaborative wargaming tools that can retain fidelity of data
  CENTER FOR COMPLEX
INTELLIGENCE ISSUES (CCII)



     ?          ?       ?       COMPLEX ISSUES


          ANALYTIC
            CORE
           GROUP



     ACADEMIC   TOOLS
      SUPPORT   GROUP
       GROUP



                        CONCEPTS
                        APPROACHES
                        TOOLS

                        ANSWERS

     CONSUMERS                                   23
             HUMAN ANALYSIS


 “...THE REPRESENTATION OF HUMAN CHARACTER
AND PERSONALITY REMAINS ALWAYS THE SUPREME
 LITERARY VALUE, WHETHER IN DRAMA, LYRIC, OR
                 NARRATIVE.”




                  BLOOM: SHAKESPEARE: THE INVENTION OF THE HUMAN




                                                              24
BACK UP SLIDES




                 25
      Intelligence Community &
        The Intelligence Cycle
                          1
                    Intelligence
     2              Requirements
                                          7
Planning &
                                    Dissemination
 Direction




    3                                       6
Collection                               Reporting


                 4               5
             Processing       Analysis
                                                     26
                          Sources of Novel Intelligence

                                        Information Sources

                                    Known            Unknown
Analytic Knowledge




                                    You Know          You Know
                     You Know         What               What
                                    You Know        You Don’t Know



                                 You Don’t Know    You Don’t Know
                     You Don’t
                                      What              What
                       Know      You Should Know    Can Be Known



                                                                     27

				
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