To demonstrate how data-enabled intelligence and planning could be employed through a data science team, this occasional paper explores the practicality of using big data analytical techniques to identify local conflict patterns with operational-level consequences. This project offers the beginning of a modeling project for predictive analysis on the correlation between essential services and the incidence of attack in an active wartime environment. By creating data layers from existing information on essential services and comparing those data points with instances of attack, this research ultimately seeks to provide better models to forecast patterns of conflict in different sociopolitical contexts.
by Mark Grzegorzewski
In this Quick Look, Mark Grzegorzewski provides a brief overview of artificial intelligence (AI)—a specific field within computer science that explores how automated computing functions can resemble those of humans. In addition to an AI history timeline, the author touches on AI subfields, AI strengths and pitfalls, and ways SOF have employed AI technologies.
In this new occasional paper, U.S. Air Force Lieutenant Colonel Low examines big data--data characterized by extensive open source datasets that are too large to analyze using traditional analytic methods. Those datasets include data comprised of news media, social media, and other open source information. By using innovative analytic tools and techniques, big datasets can be exploited to improve situational awareness and decision-making which can directly increase SOF mission effectiveness. The author advocates for the exploitation of big data during SOF pre-conflict activities. She offers lessons learned and opportunities discovered by the United Nations Global Pulse program, a program which has used big data analytics since its establishment in 2012. Through that lens, the author describes how big data can assist SOF through greater situational awareness that then leads to increased understanding of sociocultural, political, and economic issues and events.