AI Education | From Literacy to Fluency
This podcast takes listeners through eight episodes, each corresponding to a chapter of the Understanding and Working with AI program. It aims to move listeners from basic AI literacy to fluency, covering how AI systems work and how to use them with skill, judgment, and creativity. The focus is on keeping one's own voice central while learning to leverage AI effectively. The podcast is designed as an educational resource, similar to driver's education for AI.
Episodes
Episode 1 | Intelligence
Episode 1 — Intelligence What does it actually mean to "think"? This opening episode compares three kinds of intelligence—human, animal, and artificial—and discovers that comparison reveals more than hierarchy. Students meet Alia, their AI lab partner, and run their first hands-on experiments to find out where AI shines and where it stumbles. The big question driving everything: when AI feels like
Episode 2 | Teaching Machines
Episode 2 — Teaching Machines Here's the secret behind how AI really works: it doesn't follow rules a programmer wrote—it learns patterns from examples. Through the playful "Knock-Knock Joke Journey," we watch AI climb from generating random gibberish to producing coherent joke structures. The revelation is that AI recognizes correlations brilliantly but doesn't actually understand meaning, and th
Episode 3 | Prompt Engineering
Episode 3 — Prompt Engineering If AI is a powerful tool, this episode is about learning to drive it. We explore how clear, structured communication transforms the quality of what AI gives back, and why your own writing and editorial judgment are what make the difference. There's also a turn toward the human side—the real, often invisible labor behind AI systems—and a reminder that you stay the aut
Episode 4 | AI Bias
Episode 4 — AI Bias This episode shifts from "how AI works" to "whose values AI reflects." Because AI learns from human-made data, it can't be neutral—it inherits and even amplifies our assumptions and stereotypes. Through experiments with Alia, students uncover hidden biases, including a striking look at how AI can subtly shape its users through flattery and manipulative design. The goal isn't cy
Episode 5 | Magic from Math
Episode 5 — Magic from Math What looks like a crystal ball is really just probability. This episode demystifies AI predictions, showing that AI never truly "knows" the future—it calculates likelihood based on patterns it has seen. We explore why predictions fail, when to trust them, and how to build a personal framework for evaluating any AI claim. By the end, the "magic" becomes understandable ma
Episode 6 | AI Algorithms and People
Episode 6 — AI Algorithms and People Now the stakes get real. When AI helps decide who gets hired, who gets a loan, who gets into college, or how courts assess risk, the cost of a mistake changes everything. This episode examines high-stakes algorithms across hiring, criminal justice, and education, and wrestles with hard questions: What does "fair" even mean? And when an algorithm gets it wrong,
Episode 7 | AI in Media
Episode 7 — AI in Media In a world flooded with synthetic content, how do you tell real from fake? This episode builds detection skills for AI-generated images, audio, and writing, then flips to creation—exploring what makes your authentic voice something AI can't replicate. We dig into the misinformation ecosystem, the financial incentives behind fake content, and the verification tools every cit
Episode 8 | An AI-Powered Future
Episode 8 — An AI-Powered Future The finale looks ahead—honestly. We start with what AI is already doing in real research labs, from protein folding to drug discovery, then speculate responsibly about the next ten years, the next fifty, and the deeper questions of power, wealth, and control. The guiding spirit: possibilities, not predictions; both hope and concern can be true at once; and the futu
