AI/ML Archives - Shift Paradigm.

Human Factors, Space

Space: The Digital Frontier

The United States Space Force prioritizes integrating digital tools across its missions, serving as a case study for other space organizations. Their focus areas include Digital Workforce for training, Digital Headquarters for data-driven decisions, Digital Engineering for infrastructure, and Digital Operations for efficiency through automation and AI. This comprehensive approach aims to maximize the effectiveness of space operations through digital transformation.

Charles Galbreath, Senior Resident Fellow for Space Studies, Spacepower Advantage Center of Excellence (MI-SPACE), United States

AI, Human Factors, Human-Machine Teaming

Building a Layered Strategy for AI: Applications at the Strategic, Operational and Tactical Levels

AI is a formidable enabler but its potential remains far from realized. There is a growing role in using AI for improving the air force’s planning and decision-making processes at the different levels of warfare, if the inherent limitations and constraints of this technology can be appropriately managed. Allowing for as much data as possible to be exploited will be key to expanding AI adoption.

Jean-Christophe Noël, Research Associate, French Institute of International Relations (IFRI) and Editor-in-Chief, Vortex

Human-Machine Teaming, Information Superiority

Future Options for Artificial Intelligence and Machine Learning Assisted Decision-Making in Air Warfare

AI has well-known problems in that it can be fooled, cannot transfer knowledge gained in one task to another, and is entirely reliant on data for its performance. Although AI will significantly change decision-making in air warfare, not all air forces will use the same technology in the same way – even in the narrow area of decision-making.

Dr. Peter Layton, Visiting Fellow, Griffith Asia Institute, Australia

AI, Command and Control

Developing a Concept of Operations for JADC2 with an Embedded Role for Artificial Intelligence

Reaching Joint All Domain Command and Control (JADC2) goals will depend on identifying core command and control (C2) needs and establishing software development plans that are achievable. Investments in people and resources will be needed to move beyond today’s manpower intensive C2 and, as a realistic goal, improve current planning processes with automation and some AI and ML.

AI/ML