Session 1: AI Literacy Starts with Clarity (Class 1 of 3)

If you can’t explain AI simply, you don’t really understand it.

 AI isn’t magic. It’s software designed to recognize patterns, make predictions, and generate content based on data. That’s it. No buzzwords required. When we strip away the jargon, we make room for real understanding—and better decisions.

 But knowing what AI is isn’t enough.

 AI literacy also means knowing when you’re interacting with it. When your system auto-prioritizes tasks. When a tool recommends or makes decisions. When an application drafts content. When a dashboard summarizes trends. AI often works quietly in the background. Awareness is part of responsibility.

 And finally, AI literacy means asking a critical question: What was it trained on?

 Was the tool built using public internet data? Your organization’s internal documents? Resident records? Synthetic or proprietary datasets? The data behind the system shapes the outputs you receive. If you don’t know what fed the model, you don’t know what perspectives—or blind spots—it may carry.

 Clarity. Awareness. Curiosity.
That’s the foundation of AI literacy.