The Conversation outlines 3 AI models

- The Conversation published a May 2026 explainer by Hugo G. Lapierre, Normand Roy, and Patrick Charland laying out three ways schools can teach AI. - The sharpest distinction is between teaching students to use AI tools, teaching AI literacy itself, and redesigning education for an AI-shaped future. - The real policy fight is curriculum time and teacher support — not whether students already encounter AI every day.

Schools are moving past the first panic stage of AI — the phase where the whole debate was cheating, bans, and whether ChatGPT should be blocked on school Wi‑Fi. The harder question now is curricular. What exactly should children learn about AI, and where does that learning belong? That is the problem a new Conversation essay tries to sort out, by laying out three distinct models for schools rather than treating “AI in education” as one thing. ### What are the three models? The piece draws a clean line between three approaches. First, schools can teach with AI — meaning AI is mainly a classroom tool, like a writing assistant, tutor, or planning aid. Second, they can teach about AI — meaning AI itself becomes part of what students study, including how systems— which is broader and more strategic, because it asks how curriculum should change if AI is going to reshape work, knowledge, and civic life. ### Why is that distinction useful? Because schools keep collapsing these into one bucket. A district might say it is “doing AI” when it really just means teachers are using a chatbot to draft quizzes. That is not the same thing as helping students understand bias, hallucinations, training data, or automation’s effect on jobs when machines can do more cognitive work. The article’s main contribution is basically to stop that category error. ### Which model do the authors favor? Not in a simplistic “pick one and ignore the others” way. But the argument clearly leans toward AI literacy and judgment, especially for younger students. For primary-age children, the point is not deep technical instruction. It is learning simple verification habits, asking where an answer and digital tools. That pushes against the lazy version of school AI policy, where adults focus on tool adoption first and understanding later. ### Why does curriculum matter so much? Because in Canada, where the essay is situated, provinces control curriculum. That means provinces decide whether AI shows up as a few digital-skills tips, a real assessable topic, or a broader redesign of learning goals. The authors’ point is that curriculum placement determines time, advice. If it sits inside a serious literacy framework, schools can actually teach concepts, ethics, and critical thinking. ### What does “AI literacy” actually mean here? It is wider than prompt-writing. The essay points to frameworks that mix conceptual understanding with responsible use and critical judgment. UNESCO treats AI literacy as both technical and ethical. AI4K12 breaks it into five big ideas, including perception, reasoning, learning, s interface. It is whether they can understand the systems enough to question them. ### Why is

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