AI Foundations, Risks, and Prompting

This unit deepens students’ understanding of the technical, societal, and practical forces shaping generative AI, covering exponential computing and data trends, ethical and legal risks, environmental and workforce impacts, and governance considerations. Students will also develop applied skills in prompt engineering, content production, model tailoring, and human-in-the-loop quality control, building on introductory concepts and preparing for advanced model development and evaluation in subsequent units.

Learning Objectives

• Analyze how exponential trends in computing power, data growth, research investment, and infrastructure requirements influence generative AI capabilities, scalability, and environmental impact
• Evaluate legal, ethical, and societal risks—including intellectual property, bias and fairness, misinformation, privacy, safety, and workforce displacement—and propose mitigation, oversight, and self-regulation strategies
• Apply advanced prompting and content-generation techniques to produce, refine, and control AI-generated outputs (reports, blog posts, artistic content, and journalistic pieces) while implementing quality-control checks and journalism ethics
• Demonstrate methods for integrating and tailoring generative models (mini‑models, multi‑persona configurations, visual assists, and domain specialization) and design human-in-the-loop governance, deployment plans, and accountability measures