ROGUEWOLF SmartCities: Anticipating Agents of Change Adam - - PowerPoint PPT Presentation

ROGUEWOLF

SmartCities: Anticipating Agents of Change

Adam Amos-Binks Colleen Stacy Lucia Titus Kathleen Vogel Lori Wachter November 2, 2016

Outline

Motivation: SmartCities + Anticipatory thinking Approach Background: SmartCities Anticipatory thinking Intentional planning Future oriented SATs Case Study: SmartCities Agents Summary

SmartCities

IoT - $4.6 Trillion value-at-stake for public sector1 Cities will generate 63% of total value-at-stake City infrastructure transformed through IoT

1 - J Bradley, C Reberger, A Dixit, and V Gupta. 2013. “Internet of Everything: A $4.6 Trillion Public-Sector Opportunity.” Cisco, no. 23: 1–17.

Anticipatory Thinking (AT)

Deliberately thinking about the future2

2 - Klein, G., D. Snowden, and C. L. Pin. 2011. “nticipatory ThinkingA.” KL Mosier, & UM Fischer, Informed by Knowledge (2011)

Approach

Support Anticipatory Thinking (trajectory tracking) with Artificial Intelligence (intentional planning) and structured analytic techniques (AFA + backcasting) to produce Anticipatory Intelligence for an emerging use case (SmartCities)

Background

Smart Cities

• Interconnected power grids reducing power waste
• Smarter transportation resulting in increased traffic

management

• Smarter infrastructures that reduce hazards and

increase efficiency But also means:

• Expanded attack surface for malicious actors
• Cyber vulnerabilities resulting in physical consequences

Smart Cities

• Case Examples:

○ Ukraine Power Grid Hack: Cyber Used in Warfare (Dec. 2015) ○ OVH WebCam Attack: 1Tbps DDoS (Sept. 2016) ○ Dyn DDoS: IoT->DNS Attack (Oct. 2016)

• Ideal for AT as it’s coming, still time to have an impact!
• What entities will influence the value at stake?

Anticipatory Thinking

• Different from prediction, relies on expertise
• Generate a view of the future
• Identified forms:

○ Pattern Matching ○ Convergent Thinking ○ Trajectory Tracking:

“Narrative...is of particular use in trajectory tracking to understand the possible moves of other actors in the decision space”

• Klein et al. (2011)

2 - Klein, G., D. Snowden, and C. L. Pin. 2011. “Anticipatory Thinking.” KL Mosier, & UM Fischer, Informed by Knowledge (2011)

Anticipatory Thinking

• Trajectory Tracking

○ Actors actions influence our decision space ○ Does not scale, hard to incorporate new actors

Artificial Intelligence

Thinking Humanly Thinking Rationally Acting Humanly Acting Rationally

• Russell and Norvig’s AI taxonomy

Artificial Intelligence

• Automated planning: Industrial problems
• Plans: Theorized to represent plots3

○ Lead to intentional planning

3 - Schank, R, Abelson, R 1977. “Scripts, plans, goals and understanding: An inquiry into human knowledge structures.”

Intentional Planning

• Intentional path

○ Character actions are believable, goal-oriented ○ Motivated when goals are not the current state

• Intentional plan

○ Consists of intentional paths ○ Character goals conflict + collaborate

4 - Riedl, M. Young, R. M. 2010. “Narrative Planning: Balancing Plot and Character” Journal of Artificial Intelligence Research

Intentional Planning

• Need library of intentional paths!

Future-oriented SATs

• What are SATs?

○ Mechanisms to guide analysts to think about a problem.

• Why use SATs?

○ Externalize and decompose thinking ○ Help analyst mitigate cognitive limitations ○ Enable peer review

Future-oriented SATs

• Alternative Futures Analysis

○ Identified alternative trajectories ○ Based on critical uncertainties ○ Inform and illuminate decisions, plans and actions today

• Backcasting

○ Scenario analysis ○ Desirable futures ○ Plot a point in time, work backward to present

Case Study

Knowledge Engineering

Alternative Futures Analysis

Security of the Internet Clockwork Orange Shangri La Government Involvement Independent Leviathan

Corporate Bliss

(corporate dominance with little risk)

Nation State Security

(increasing regulatory control)

How might the world of the Internet evolve?

Bottom line uncertainty

(hackers have leverage )

Regulations without bite

(government regulates to no avail)

5 - Healey, Jason, and Hughes Barry. 2015. “Risk Nexus: Overcome by Cyber Risks? Economic Benefits and Costs of Alternate Cyber Futures.” The Atlantic Group.

Internet Evolution

Axes:

• Security

○ Shangri La - Clockwork Orange

• Gov. Involvement

○ Independent - Leviathan

Industry Sector Actors

Sectors:

• Electricity
• Water
• Transportation

Strategic Plans

Strategic plans Intentional plans

Corporate strategies (e.g. Apple, Duke Energy, Toyota) Government future vision policy docs (e.g. Raleigh 2030) NGO/NPO strategies (e.g. WRF) Non-state actor strategies (e.g. ISIS 2020)

Intentional Paths

Actor: Water Research Foundation (NGO) Sector: Water Goal: Shangri-La (H), Leviathan (H)

Intentional Paths

Actor: ISIS (Militant) Sector: Transportation Goal: Clockwork Orange (H), Leviathan (H)

Intentional Paths

Actor: Government Sector: Transportation Goal: Shangri-La (M), Independent (L)

Insights (Cooperation)

Water Research Foundation & Government, water Leviathan

Insights (Conflict)

ISIS vs Government, Transportation

Use Case

• Hand crafted knowledge engineering

○ SmartCities actors (sectors from DHS) ○ SATs (AFA, backcasting) ○ Strategic plans → Intentional paths ○ Trajectory tracking (conflicts, collaboration)

Summary

• Trajectory tracking w/ intentional planning
• SmartCity knowledge engineering using SATs
• Strategic plans → intentional paths

Next Steps

DO7

• OpenKE: automate strategic→intentional paths
• Input for trajectory tracking in serious game

Discussion

Questions? Email: {aaamosbi, cstacy, lltitus, kmvogel, lawachte}@ncsu.edu