AI for Decision Support in Defense Operations

Agenda

Day 1: Foundations & Mission Context

• Introduction & Course Orientation (45m): We'll explore how AI fits into the broader landscape of military technology and why it matters for operational effectiveness.
• AI & Machine Learning Essentials (1.5h): Learn how data and algorithms translate into actionable mission outcomes, with real-world examples from defense applications.
• Data Fusion for Situational Awareness (1.5h): Explore methods for handling uncertainty, conflicting information, and time-critical decision requirements.
• Defense Use Cases Deep Dive (2h): Interactive case study discussions covering both successes and lessons learned from field implementations.
• Mission Mapping Exercise (1h): Hands-on group activity where teams analyze a sample mission scenario, identify key decision points, and propose AI support strategies. Teams present their findings and receive peer feedback.

Day 2: Building AI-Enabled Decision Support

• From Mission Needs to AI Requirements (1h): Learn problem framing techniques, data needs assessment, and how to define success measures that align with mission objectives.
• Human–Machine Teaming (1h): Explore explainability requirements, trust-building strategies, and maintaining appropriate commander oversight while leveraging AI capabilities.
• AI System Lifecycle & Assurance (1h): Cover testing methodologies, validation approaches, red-teaming techniques, and continuous monitoring strategies.
• Contested Logistics Scenario Workshop (2h): Teams work through the complete process of outlining an AI-enabled decision-support approach, from problem identification to solution architecture.
• Security & Ethical Considerations (1h): Operational security implications, adversarial AI risks, and DoD AI Ethical Principles in practice. Case studies of security challenges and mitigation strategies for AI-enabled systems.
• Measuring Impact & ROI (1h): Learn to assess improvements in readiness, decision speed, accuracy, and cost-benefit analysis for defense applications.

Day 3: Operationalization & Roadmapping

• Governance & Oversight (1h): Learn to navigate the regulatory landscape and ensure compliance.
• Building an AI-Ready Organization (1h): Practical tools for building internal capabilities.
• Capstone Project (2.5h): Teams work through requirements analysis, solution design, implementation roadmap, and risk assessment.
• Team Presentations & Peer Feedback (1.5h): Structured peer feedback sessions help refine approaches and identify implementation challenges.
• Future Trends & Closing (1h): Discussion of future opportunities, challenges, and how to stay current with AI developments in defense applications.