Institute for 2009 I I Patterns of Interaction Collaborative & - PowerPoint PPT Presentation

Institute for 2009 I I Patterns of Interaction Collaborative & Perception of Intent Innovation Michael O’Brien Kok Keng Tan Tal Sack Matthieu Branlat Lauren Grinstein Michael Smith

Institute for 2009 I I Intent from COMINT Patterns of Interaction & Perception of Intent Collaborative Challenges to 3rd Party Observers in Inferring Goals and Constraints Innovation Understanding intent is hard because it is complex . Looking at the patterns involved in interpretation of signals , and interactions between agents , helps structure things in a meaningful way.

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Institute for 2009 I I Intent from COMINT Patterns of Interaction & Perception of Intent Collaborative Challenges to 3rd Party Observers in Inferring Goals and Constraints Innovation Framework for Understanding Issues of Reading Intent Case Studies of Intent Misperception • Ruby Ridge • Yom Kippur/October 1973 War Lab Studies of Interaction and 3rd Party Analysis • Cooperative/Competitive Game • Drone Mission Negotiation Scenario Directions for Support (Design Seeds)

What is Intent? Powerful explanatory mechanism for forecasting behavior So useful we use it everywhere, even when it might not be really accurate

What is Intent?

What is Intent? Opportunities Constraints Evolving Sets Changing of Goals State of World Multiple Roles Evolving Understanding of World Actions of Agents

Continuum of Ways to Read Intent Direct Perception Projection Perspective Taking

Continuum of Ways to Read Intent Experts • Social Scientists • Historians • Global Leaders •Consider immediate and larger contexts Perspective Taking •Use mental simulation •Apply domain knowledge when assessing information

Framework for Understanding Issues of Reading Intent Political Psychology models of signaling and (mis)perception Cognitive Systems Engineering models of distributed anomaly response and process tracing

Signaling & (Mis)Perception  ⚔  $    $ ...

Patterns of Misperception of Intent misperception of others' over-centralization; perceptions of us presumption of coherence, planning, unitary action over-estimation of own importance over-confidence over- (in reading & homogenization signaling intent) view others as static, projection, unchanging lack of mirroring empathy stereotyping fundamental attribution error assumption of proportionality in effort and importance predisposition for causal explanations

Distributed Process Monitoring & Replanning Intentional Goals shape resolves Stance Plans Nature of Constraints structure support Activities Analyses spawn set (diagnostic/ predictive) Events Expectations get set integrated context Data Data Causal Time

More Detailed Model of Signaling & Perception Expectations- Attention Stance Analysis Events Data Goals Plans Activities Expectations- Attention

More Detailed Model of Signaling & Perception Expectations- Attention Expectations- Stance Analysis Events Data Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Expectations- Activities Plans Attention Attention Expectations- Expectations- Stance Analysis Events Data Attention Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Expectations- Activities Plans Attention Attention Expectations- Expectations- Stance Analysis Events Data Attention Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Activities Plans Attention Expectations- Attention

More Detailed Model of Signaling & Perception Expectations- Attention Expectations- Stance Analysis Events Data Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Expectations- Activities Plans Attention Attention Expectations- Expectations- Stance Analysis Events Data Attention Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Expectations- Activities Plans Attention Attention Expectations- Expectations- Stance Analysis Events Data Attention Attention Goals Plans Activities Data Events Analysis Stance Goals Expectations- Activities Plans Attention Expectations- Attention

Methodological issues • How can we study the process of inferring intent? • How can we model dynamics of behavior that reveal underlying dimensions of intent (stance, mindset, goals)?

Studies • Case studies • Ruby Ridge • Yom Kippur • Experiments • Collaborative/Competitive Game • Negotiation Scenario

Studies • Case studies • Ruby Ridge • Yom Kippur ➠ poster session • Experiments • Collaborative/Competitive Game • Negotiation Task ➠ poster session

Case Study: Ruby Ridge Motivations • Purposes • Analyze dynamics of interaction • Explore representations • Scope • Available documentation • Multiple perspectives • Implement process-tracing methodology

Case Study: Ruby Ridge Result: Perspectives LAW ENFORCEMENT / FBI General attention to white supremacists, militia movements, conspiracy theorists... File built on Weaver (Aryan Nations) Initial troubles with Weaver Threatening letters received by judge(s) Initial Marshall Shooting Weaver will killed Weaver is a resist arrest serious threat Protect society from Weaver Get additional Get FBI resources involved

Case Study: Ruby Ridge Result: Perspectives WEAVER FAMILY Moved away from corrupt society Autonomous life Tricked by local police Growing animosity and mistrust against governmental agencies Knew he was in trouble with the law Thought he would not have a fair trial Initial Shooting Son killed Police will shoot them Increased animosity and mistrust of government Law enforcement Protect will come with themselves hostile purposes from law enforcement Check Lock themselves movement in cabin on property

Case Study: Ruby Ridge Result: Patterns conflict alignment conflict time

Experiment Collaborative/Competitive Game • Purposes • Analyze dynamics of interaction from multiple perspectives • Rules designed to produce cooperative and competitive behaviors • Experiment • Participants verbalize • Activity is captured, then analyzed by outside observer

Experiment Collaborative/Competitive Game Round 1

Experiment Collaborative/Competitive Game Round 2

Inferring intent is difficult • We are very attuned to it... • we are very good at it in many situations • we will infer intent • ... but it is easy to misperceive intent • people’s behavior is not always deliberate • history of interactions creates powerful expectations • “language” of interaction can be ambiguous • Especially difficult for third party observers

Patterns of Misperceptions of Intent misperception of others' over-centralization; perceptions of us presumption of coherence, planning, unitary action over-estimation of own importance over-confidence over- (in reading & homogenization signaling intent) view others as static, projection, unchanging lack of mirroring empathy stereotyping fundamental attribution error assumption of proportionality in effort and importance predisposition for causal explanations

What supports intent reading • Mental simulation • Structure (patterns, dynamics) • Reflection Perspective Taking

Directions for Support Rigor as Framework for Reflection Archetypical Patterns as Hypothesis Space Anchors Post-Hoc Automated Critique

Archetypical Patterns as Hypothesis Space Anchors Rivalry Balancing Escalation process Rapprochement Recognition of misread signal Misperceptions

Post-Hoc Automated Critique Patterns of Misperceptions of Intent misperception of others' over-centralization; perceptions of us presumption of coherence, planning, unitary action over-estimation of own importance over-confidence over- (in reading & homogenization signaling intent) view others as static, projection, unchanging lack of mirroring empathy stereotyping fundamental attribution error assumption of proportionality in effort and importance predisposition for causal explanations

Institute for 2009 I I Intent from COMINT Patterns of Interaction & Perception of Intent Collaborative Challenges to 3rd Party Observers in Inferring Goals and Constraints Innovation Understanding intent is hard because it is complex . Looking at the patterns involved in interpretation of signals , and interactions between agents , helps structure things in a meaningful way.

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