Building AI Literacy That Lasts Beyond Today’s Tools
- Guest name: Chuck Melley
- Guest title: Senior VP, Policy, Advocacy and Communities
- Guest company: CodeAI
- Host: Eric Stano
Brief description of the episode
For curriculum leaders, building AI literacy into a school curriculum is a lot to carry. The tools keep changing, and every plan you write has to account for technology that will look different by next year. So it’s natural to wonder which parts of that plan will last, from the concepts students learn to the examples in each lesson and the policies behind them.
This episode is for anyone working through that question. Chuck Melley, Senior VP of Policy, Advocacy and Communities at CodeAI, works with states and countries on putting AI and computer science education in place. He explains which parts of an AI literacy plan belong at the center and which need regular updating, so you can plan with more confidence.
He also walks through the pieces school AI literacy plans often leave out, including funding for teacher training, a named owner for AI literacy, and time in the school day to teach it. With PISA set to assess AI literacy in 2029, it’s a useful listen for anyone deciding what to put in place now.
Key Takeaways:
-
- Build a stable core around how AI works: data, algorithms, prediction, and bias.
- Keep examples, tools, and activities in a modular layer that you can refresh on a regular cycle.
- Use digital delivery to update content without waiting for a new edition.
- Focus learning on concepts and habits that carry over to whatever tools come next.
- Measure success by whether students can explain how AI works, alongside how well they use it.
Get the Citation‑First AI Checklist
Build AI answers that show their work: citations, guardrails, and a QA rubric designed for education products.
