STIA-475 Information Technology and International Security
Fall for 2017-2018
Thomas Carroll & Christina Ray
This course examines information technology’s role in transforming the global financial system and in providing new tools to help policymakers understand and anticipate the still unfolding international security implications of this transformation. The IT revolution that led to financial innovation, deregulation, and the proliferation of financial markets around the world continuously spawns capabilities for sense-making. New (and new combinations of) methods, models and tools for the collection, aggregation, processing and sense-making of financial market data emerge. One can analyze tens of millions of financial instruments with millions of price updates per second, streaming topic-coded news in foreign languages, supply chains, private equity and venture capital investments, social media, and projects offers and tenders from around the world. Economic indicators, which have long been staples for policy makers are losing ground to near real time financial indicators of systemic risk, nation state stability, disease spread, agricultural prospects and other critical topics. Through combining social science, quantitative finance, data science and IT, teams are increasingly able to harness financial data to keep policy makers informed and better able to anticipate national security events and crises.

The objective of this course is to introduce students to empirical methods, models, and tools from the peer reviewed literature and the financial and security domains by demonstrating their utility using real data against real world use cases. This course will acclimate students to challenges and opportunities inherent in trying to provide situational and option awareness to policymakers in a decision-theoretic framework. Professors will introduce students to ontologies, typologies, taxonomies, data models, and industry classification schema, and demonstrate how they are used with IT and financial data to answer real world questions. Causation, correlation and various approaches to anticipatory analysis will be explored and demonstrated. A guest lecturer will provide a succinct and practical lecture on “big data”. Professors will demonstrate Bayesian, machine learning and other approaches for sense-making and anticipatory analysis as well as financial industry analytics and visualization tied to real world use cases. Lectures and demonstrations will be followed by student exercises and problem solving employing the types of methods, models, tools and data demonstrated in class.

Learning Goals

By the end of this course, engaged students who come regularly to class, participate in class discussions and complete all readings and assignments will be able to:

· Articulate the importance of financial markets to international security

· Work in multidisciplinary teams with structured and unstructured financial data to explore complex international security problems
· Think strategically about and evaluate methods, models, tools and data sources for answering complex international security questions

· Understand the purpose of and approaches for anticipatory analysis

Credits: 3
Prerequisites: None
More information
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