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Big Data for Generals … and Everyone Else over 40: U.S. Department of Defense
* Paperback 180 Pages *
December 2021 Release
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 rate of scientific advancement in the various forms of military-oriented AI has increased markedly in recent years, and it appears now that many military professionals presume that AI applications constitute a necessary precondition for military success in future high-end conflict.
Special Operations Forces (SOF) have similarly attempted to harness the power of AI, machine learning, natural language processing, and deep learning for their unique mis-sion sets. While sound in principle, employing AI-based solutions efficiently and effectively first requires clear knowledge of (a) how they work, (b) the conditions for which are they are and are not appropriate, (c) the challenges of employing them in the field, and (d) how to employ them within ethical boundaries.
The purpose of this edited volume is to demystify the capabilities and limitations of AI-based military solutions. The chapters are written with the assumption that readers have a limited background with the underlying scientific, modeling, and data science principles that make AI-based solutions viable. The contributors to the volume are scholars and expert practitioners who work closely with the Joint Special Operations University to write for the specific needs of the SOF community.
Nevertheless, this volume has applicability across the U.S. Government since the SOF community operates under nearly the same conditions as the rest of the government sector. 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 SOF enterprise.
Executive Summary
The purpose of this monograph is to help leaders and managers in the U.S. Special Operations Forces (SOF) enterprise become comfortable and conversant with the vocabulary and concepts associated with Big Data. It is not designed to make the reader a data scientist. Rather, it enables the reader to make better use of, provide the appropriate support and environments for, and more richly receive the advice of personnel who are trained in data science. A main finding of the research is that there is a substantial disconnect between the popular imagination of predictive analytics and what cutting edge science and technology can actually deliver.
The magic of find, fix, finish, exploit, analyze and disseminate; social media trend analysis; the potential power of metadata analysis; and other powerful computer assisted analytic tools, such as Project Maven, seem to suggest that the military is on the cusp of an extraordinary era where an enemy’s behavior can be predicted with a high degree of probability. Perhaps this is true, but it is more likely not. Certainly, insight can be gleaned from trend analysis and correlations, but it is essential to remember that the human behaviors underlying the predictive analytics most everyone experiences—through Google, Amazon, and other providers—are very different than the human behaviors with which SOF contend.
December 2021 Release
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 rate of scientific advancement in the various forms of military-oriented AI has increased markedly in recent years, and it appears now that many military professionals presume that AI applications constitute a necessary precondition for military success in future high-end conflict.
Special Operations Forces (SOF) have similarly attempted to harness the power of AI, machine learning, natural language processing, and deep learning for their unique mis-sion sets. While sound in principle, employing AI-based solutions efficiently and effectively first requires clear knowledge of (a) how they work, (b) the conditions for which are they are and are not appropriate, (c) the challenges of employing them in the field, and (d) how to employ them within ethical boundaries.
The purpose of this edited volume is to demystify the capabilities and limitations of AI-based military solutions. The chapters are written with the assumption that readers have a limited background with the underlying scientific, modeling, and data science principles that make AI-based solutions viable. The contributors to the volume are scholars and expert practitioners who work closely with the Joint Special Operations University to write for the specific needs of the SOF community.
Nevertheless, this volume has applicability across the U.S. Government since the SOF community operates under nearly the same conditions as the rest of the government sector. 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 SOF enterprise.
Executive Summary
The purpose of this monograph is to help leaders and managers in the U.S. Special Operations Forces (SOF) enterprise become comfortable and conversant with the vocabulary and concepts associated with Big Data. It is not designed to make the reader a data scientist. Rather, it enables the reader to make better use of, provide the appropriate support and environments for, and more richly receive the advice of personnel who are trained in data science. A main finding of the research is that there is a substantial disconnect between the popular imagination of predictive analytics and what cutting edge science and technology can actually deliver.
The magic of find, fix, finish, exploit, analyze and disseminate; social media trend analysis; the potential power of metadata analysis; and other powerful computer assisted analytic tools, such as Project Maven, seem to suggest that the military is on the cusp of an extraordinary era where an enemy’s behavior can be predicted with a high degree of probability. Perhaps this is true, but it is more likely not. Certainly, insight can be gleaned from trend analysis and correlations, but it is essential to remember that the human behaviors underlying the predictive analytics most everyone experiences—through Google, Amazon, and other providers—are very different than the human behaviors with which SOF contend.
180 pages, Paperback
Published December 1, 2021
1 person want to read
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Displaying 1 of 1 review
November 27, 2024
In light of preventing several of our military leaders from going full tech-bro, the special operations school got together several engineers and tech doctorates to explain to the brass the benefits, limits, and potentials, of various new technologies and their disruptive potential in the next 5-15 years:
*Artificial intelligence: suicide prevention, facial recognition, pattern analysis
*Deep Learning: deep learning, crowd flow
*Machine learning: predictive equipment, swarming technology, social media tracing, force readiness
*Theoretical: modeling, simulation, quantum computing, enterprise cloud, encryption issues/security, CTN strategy gaming etc.
Despite the title, I found it insightful, informative and well done despite the candor of military writing. It's a unique perspective, the operating environment of special operations forces violates the assumptions that make Silicon Valley’s algorithms so effective. In the end, Silicon Valley’s challenges relate more readily to patterned, replicated behavior, whereas the challenges of SOF (and war in general) are rooted in open systems where new, adaptive behavior is the norm thereby undermining the effectiveness of algorithmic modeling.
*Artificial intelligence: suicide prevention, facial recognition, pattern analysis
*Deep Learning: deep learning, crowd flow
*Machine learning: predictive equipment, swarming technology, social media tracing, force readiness
*Theoretical: modeling, simulation, quantum computing, enterprise cloud, encryption issues/security, CTN strategy gaming etc.
Despite the title, I found it insightful, informative and well done despite the candor of military writing. It's a unique perspective, the operating environment of special operations forces violates the assumptions that make Silicon Valley’s algorithms so effective. In the end, Silicon Valley’s challenges relate more readily to patterned, replicated behavior, whereas the challenges of SOF (and war in general) are rooted in open systems where new, adaptive behavior is the norm thereby undermining the effectiveness of algorithmic modeling.
Displaying 1 of 1 review