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Technology innovation and the future of Air Force intelligence analysis. Volume 2, technical analysis and supporting material / Lance Menthe [and 10 others].

RAND Reports Available online

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Format:
Book
Author/Creator:
Menthe, Lance, author.
Contributor:
Project Air Force (U.S.). Force Modernization and Employment Program.
Rand Corporation.
United States. Department of the Air Force.
Language:
English
Subjects (All):
Artificial intelligence--Military applications--United States.
Artificial intelligence.
Military intelligence--United States--Evaluation.
Military intelligence.
United States. Air Force--Intelligence specialists.
United States.
Other Title:
Technology Innovation and the Future of Air Force Intelligence Analysis
Place of Publication:
Santa Monica, Calif. RAND Corporation 2021
Summary:
There is growing demand for the Air Force Distributed Common Ground System (AF DCGS) to analyze sensor data. Getting the right intelligence to the right people at the right time is increasingly difficult as the amount of data grows and timelines shrink. The need to exploit all collections limits the ability of analysts to address higher-level intelligence problems. Current tools and databases do not facilitate access to needed information. Air Force/A2 asked researchers at RAND Project AIR FORCE to analyze how new tools and technologies can help meet these demands, including how artificial intelligence (AI) and machine learning (ML) can be integrated into the analysis process. PAF assessed AF DCGS tools and processes, surveyed the state of the art in AI/ML methods, and examined best practices to encourage innovation and to incorporate new tools.
Contents:
Chapter One: Introduction
Chapter Two: Overview of the AF DCGS Today
Chapter Three: Improving Efficiency, Effectiveness, Human Capital, and Agility: Lessons from Historical Case Studies
Chapter Four: Artificial Intelligence and Machine Learning: A Primer for AF DCGS Analysts
Chapter Five: Improving GEOINT Analysis: Additional Detail
Chapter Six: Rebalancing AF DCGS Competencies and Organization: Additional Detail
Chapter Seven: Building the Right Skills: Additional Detail
Chapter Eight: Fostering Innovation and Successful Implementation: Additional Detail
Appendix A: Defining Technology Readiness Levels for Artificial Intelligence/Machine Learning.
Notes:
Description based on electronic resource.

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