AI Literacy Is Not Coding Class

Somewhere along the way, "AI literacy" got confused with "learning to code." Teachers hear the phrase and picture Python lessons they have no time to teach. That's a myth worth killing.

AI literacy is not about building models. It's about living wisely with systems you didn't build. A literate teacher can answer five questions about any AI tool: What data does it take in? What does it do with that data? What is it optimizing for? Where can it go wrong? And who is accountable when it does?

Notice: none of those requires a computer science degree. They require curiosity and a little vocabulary — the same muscles teachers already use when they evaluate a textbook or a field trip vendor.

The confusion matters because it keeps the wrong people out of the conversation. When AI literacy sounds technical, it becomes the IT department's job. But the people who decide what student data enters a chatbot are teachers, in classrooms, at 9 p.m. They are the front line, and they need the literacy more than anyone.

So stop picturing coding class. Picture a 45-minute workshop where teachers practice stripping names from prompts, reading a vendor's data policy, and spotting when an AI output looks confident but wrong. That's AI literacy. Every adult in a school building needs it.

I explain frameworks; I don't give legal counsel.