Module 1 Narration#
Opening#
Open with the professional setting: an AI review team evaluating a proposed applied AI system before pilot deployment. Ask students what decision is being made, who is affected, and what evidence would be persuasive to a skeptical reviewer.
Middle#
Move through the module in four passes:
Define AI paradigms and system boundaries in the context of Foundations of Artificial Intelligence.
Walk through the lab as a proxy-data exercise, emphasizing what it can and cannot show.
Compare a baseline with an AI-enabled or more sophisticated alternative.
Translate the result into stakeholder language: recommendation, risk, mitigation, and next evidence.
Closing#
Close by returning to the module artifact: AI system review package with architecture, evidence, limitations, and deployment recommendation focused on ai paradigms and system boundaries: Map symbolic, statistical, and neural AI approaches against a realistic stakeholder problem.. Students should leave knowing exactly what artifact they are producing and how it will be judged.