AIQ
AIQ
Everything a teacher needs to deliver this lesson — pick your grade's script below once you've read the background.
This is the fourth lesson in World 1 ("What Is AI?"), and it works differently from the first three. Instead of introducing new information, it hands students a single test and asks them to apply it to a run of examples designed to surprise them — some that look high-tech but aren't AI, and some that look completely ordinary but are. By the end of the lesson, students across all four age bands should be able to:
You don't need a technical background to deliver this lesson well — the app does the explaining. What you need is a clear enough grip on the underlying test that you can answer a student's "wait, why isn't that AI?" without guessing. Here is that test, in plain language.
The lesson's working definition of AI is: a system that improves its behavior by learning from data or examples, rather than by having every response pre-written by a programmer. A calculator always does the same thing with "2 + 2" no matter how many times you type it — a human wrote the addition rule once, and the calculator just executes it, forever, unchanged. That's not AI, no matter how fast or how digital it is. A spam filter, by contrast, gets better at recognizing spam the more email it sees, because it was trained on huge numbers of examples of spam and non-spam and adjusted its own internal rules to fit the pattern. That adjustment-from-examples step is what the lesson means by "learning," and it's the entire dividing line the game is testing.
This is a simplification of a much messier real debate among computer scientists — historically, "AI" also included hand-built rule systems that never learn anything from data (these are called expert systems or symbolic AI, and they were the dominant form of AI research for decades). The lesson sidesteps that history on purpose: for a K-12 audience, "does it learn from data" is the distinction that actually helps a student recognize modern AI in the wild, since almost everything today's students will encounter — recommendation feeds, spam filters, voice assistants, image generators — falls on the "learns from data" side, and almost everything they'd mistake for AI because it's electronic or precise (calculators, digital clocks, LED bulbs, timer-based traffic lights) falls on the other side.
The lesson's examples are deliberately chosen to break two lazy heuristics kids (and adults) commonly use: "looks futuristic = AI" and "boring and everyday = not AI." A voice-changer filter and an auto-DJ music mixer both quietly run machine learning models to do their job, even though neither looks like "AI" in the sci-fi sense. Meanwhile a digital clock, an LED bulb, and a calculator watch all look modern and electronic but are running fixed logic that hasn't functionally changed in decades. The email inbox that automatically routes newsletters away from your main tab, the phone feature that learns which apps you open in the morning and preloads them, and the drone a farmer flies over a rice field to spot crop disease from the air are all real, current uses of machine learning — none of them are exaggerated for the lesson.
One more thing worth knowing before you teach this: the lesson is intentionally testing the boundary in both directions in the same activity. Younger students especially tend to assume "smart-sounding name = AI" (a "smart" toilet, a "smart" bulb) — the LED bulb example exists specifically to break that assumption, since an LED is just an efficient light source, not a learning system, despite "smart" often being marketed loosely.
This lesson needs almost nothing beyond what students already use to access AIQ:
Time: the in-app lesson itself runs 5–10 minutes. Budget 15–25 minutes total for a full classroom delivery once you add the hook, guided discussion, and wrap-up described in each age-band script.
No prior AI or computer science knowledge is required from you as the teacher — every example the app uses, and every example in the age-band scripts below, is explained in the "Teacher Background" section above, and each age-band script gives you specific lines you can say out loud rather than expecting you to improvise a technical explanation on the spot.