Module 1 Narration

Slide 1 Narration

Open by telling students that “AI” is best understood as an umbrella term. The field contains multiple problem definitions and technical traditions. This module will help them build a vocabulary for distinguishing those traditions.

Slide 2 Narration

Introduce symbolic, statistical, and hybrid AI as orienting categories rather than rigid boxes. Emphasize that many current systems borrow methods across these traditions.

Slide 3 Narration

Explain that foundational distinctions matter because decision-makers often talk about AI as if every system has the same strengths and limitations. Students should leave the course able to ask what kind of intelligence a system actually depends on.

Slide 4 Narration

Frame the history of AI as a cycle of problem framing, optimism, technical bottlenecks, and reconfiguration. The field advances when methods align with available data, compute, and evaluation needs.

Slide 5 Narration

Pause for discussion. Encourage students to compare intelligence in humans, organizations, and machines. Invite them to name examples where prediction alone is insufficient without planning or explanation.