Foundations of Causal AI

This unit introduces the core concepts, history, and business rationale for causal artificial intelligence and contrasts it with traditional analytics. Students will explore the value chain, team roles, data and visualization needs, and initial steps to launch causal AI projects, preparing them for technical modeling and deployment in later units.

Learning Objectives

• Analyze distinctions between causal AI and traditional analytics by comparing goals, assumptions, outputs, and limitations in real-world examples
• Demonstrate core concepts and origins of causal AI by creating a concept map that explains definitions, key principles, and why causal approaches are the next generation of AI
• Evaluate business imperatives, value propositions, and prioritized use cases for causal AI by assessing potential impact, feasibility, and organizational fit for a hypothetical enterprise
• Apply project initiation strategies for causal AI by outlining the scope of services, hybrid team roles, and data/visualization/framework requirements for a pilot implementation