Whitlock C. Winning the National Security AI Competition....2023 torrent

Textbook in PDF format

Successfully identify, structure, and execute Artificial Intelligence (AI) programs and projects necessary for the nation to secure an advantage in a highly competitive space. Over eight chapters, this book conveys the principles and best practices needed by government and industry leaders at multiple levels. The book begins with a case for action and a differentiated way for AI leaders and their customers to think and communicate about AI. We then address the programming and budgeting elements of this challenge facing senior executives and program managers.
For those engaged in actual AI work, the project and data science chapters cover the essential elements needed to guide teams and contribute effectively as a leader. Lastly the book covers critical enabling areas: leading data science practitioners and others on the AI team, and navigating technology choices through an understanding of the underlying technologies in the AI solution stack.
AI solutions and work are critical to national and international security over the coming decades. Winning the National Security AI Competition describes the importance of this area and recommends actions to mobilize the national security enterprise for action.
What You’ll learn
Axioms or enduring truths at work in six dimensions of AI: program, budget, project, data science, people, and technology; leaders must make decisions and drive work in the context of these truths.
Best practices―such as decision frameworks, processes, checklists―for leading work in each of the six dimensions.
How the axioms and best practices are contextualized to national security missions.
Who This Book Is For
Government and industry leaders in national security who are involved in or assigned to AI-related work. This includes data scientists who aspire to lead; software engineers and leaders through whom AI solutions are deployed; mission experts assigned to work with AI teams; senior decision makers on programs and projects; project level leaders; and IT leaders essential to enabling production AI solutions