Special Operations Forces Transformation in the Future Operating Environment by Dr. Peter McCabe
In this edited volume, the authors pose solutions to Special Operations Forces’ (SOF) future challenges. Looking to the national defense strategy, this volume describes the role of competition in the future and the three ways SOF can compete, deter, and win. SOF must maintain their edge, and their transformation needs to be addressed at the individual, organizational, and institutional levels. This volume takes risk into consideration while addressing SOF transformation in three key areas: SOF roles and missions, culture, and great power competition. Both U.S. and Canadian SOF perspectives are outlined in this volume, and each chapter urges readers to consider how SOF might better compete short of armed conflict.
The artificial intelligence (AI) arms race is well under way with great powers, secondary powers, and even non-state actors actively pursuing the weaponization of this technology in a variety of ways. The purpose of this edited volume is to demystify the capabilities and limitations of AI-based military solutions. With a conversational tone and progressive learning trajectory across the chapters, Big Data for Generals … and Everyone Else over 40 provides an accessible but comprehensive overview of the concepts and considerations for making emerging technology a true force multiplier for the Special Operations Forces enterprise.
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.