Foundations of Causal AI

This unit introduces the fundamentals, business value, and context of causal artificial intelligence, contrasting it with traditional analytics and outlining its origins and core concepts. Learners will explore the roles, services, and data/visualization frameworks needed to launch causal AI efforts, preparing them for technical modeling and implementation in subsequent units.

Learning Objectives

• Analyze key differences between causal AI and traditional analytics, including their questions, outputs, and decision-making implications
• Evaluate the business imperative and value propositions of causal models, including the role of augmented intelligence and hybrid teams in delivering outcomes
• Demonstrate understanding by defining causal AI, summarizing its origins and core concepts, and articulating why it is considered the next generation of AI
• Apply principles of data, visualization, and framework design to draft an initial scope-of-services and project plan that identifies required data, team roles, and first steps for a causal AI initiative