Last week, I was in a classroom with a group of students that need more AI knowledge to augment what they learned in the regular curriculum. Personal Mission. Not the kind of \u201clecture hall\u201d classroom, but the messy, buzzing kind, laptops open, coffee cups scattered, and a quiet background hum of ChatGPT tabs working overtime.<\/p>\n\n\n\n
One student waved me over. \u201cWiemer, look, ChatGPT wrote my entire market analysis in two minutes.\u201d<\/p>\n\n\n\n
It looked good. Professional. Structured. Numbers, charts, even footnotes.<\/p>\n\n\n\n
But then I asked the simplest question in the world: \u201cWhich of these claims are actually true?\u201d<\/p>\n\n\n\n
Blank stares. A nervous chuckle. A quick scan of the text.<\/p>\n\n\n\n
And then that dawning realization: they didn\u2019t know.<\/p>\n\n\n\n
That\u2019s when it hit me.<\/p>\n\n\n\n
If you drop today\u2019s students into the GenAI ocean without a life jacket, they won\u2019t drown because they can\u2019t swim. They\u2019ll drown because they can\u2019t tell the difference between a wave and a whirlpool.<\/p>\n\n\n\n
And that life jacket? It\u2019s called critical thinking<\/strong>.<\/p>\n\n\n\n Not the \u201cwrite an essay about Socrates\u201d kind I had to do in high-school. Not the dusty logic exercises you half-remember from first year. But the practical<\/em>, AI-era version.<\/p>\n\n\n\n I watched as one student scrolled through the AI\u2019s answer, eyes darting over the neatly formatted paragraphs. At first glance, it looked flawless. But as we read together, I pointed to one sentence. \u201cIs that a fact, or just the AI\u2019s opinion dressed up as fact?\u201d She hesitated. Another line. \u201cNotice how vague that is, what would you need to ask to make it precise?\u201d By the third question, she was leaning forward, spotting the gaps herself. This is where good reasoning starts: learning to separate truth from fluff, to close the gap with sharper, more deliberate questions.<\/p>\n\n\n\n Later, another group showed me an AI-generated project plan. Impressive, until we traced the logic behind its recommendations. \u201cWait,\u201d one student said, \u201cstep three doesn\u2019t actually follow from step two.\u201d Exactly. AI can sound confident while skipping over its own contradictions, and unless you know how to follow the thread, you won\u2019t notice the knots.<\/p>\n\n\n\n Then there was the marketing forecast. Beautiful graphs, persuasive language, confident predictions. But confidence isn\u2019t certainty. I asked, \u201cIs this a rock-solid conclusion or just the AI\u2019s best guess?\u201d They went back to check the data, and discovered it was a guess built on shaky comparisons.<\/p>\n\n\n\n And finally, the social media example: a perfectly crafted quote from a \u201crecent study.\u201d Except the study didn\u2019t exist. The quote was invented. The students looked at me, half amused, half alarmed. It took us 30 seconds to verify, but imagine if they\u2019d shared it without checking. In a world where AI can create convincing fakes faster than we can read them, verifying before amplifying isn\u2019t just a skill: it\u2019s survival.<\/p>\n\n\n\n The 4 elements I want to put into the curriculum could look like this, very much work in progress:<\/p>\n\n\n\n Part 1 \u2013 The basics of good reasoning \u2192 AI prompt literacy & source sanity checks. Can you read an AI answer and separate facts from opinions? Spot the vague phrasing? Ask a better follow-up question to close the gap?<\/p>\n\n\n\n Part 2 \u2013 Deductive reasoning \u2192 Logic-checking AI outputs. If AI makes a recommendation, can you trace the chain of reasoning? Spot where it skipped a step? Catch the moment it contradicted itself?<\/p>\n\n\n\n Part 3 \u2013 Inductive reasoning \u2192 Judging AI predictions under uncertainty. GenAI is a master of probabilities, not certainties. Can you tell the difference between a solid conclusion and a \u201cbest guess dressed in confidence\u201d?<\/p>\n\n\n\n Part 4 \u2013 Application \u2192 Surviving the flood of AI-generated misinformation. Deepfakes, fake studies, fabricated quotes\u2014AI can make them in seconds. Can you verify before you amplify?<\/p>\n\n\n\n <\/p>\n\n\n\n We teach math, so students can count their money.<\/p>\n\n\n\n We teach language, so they can express themselves.<\/p>\n\n\n\n But in the GenAI era, we must<\/em> teach critical thinking so they can survive their own tools.<\/p>\n\n\n\n <\/p>\n\n\n\n Because AI won\u2019t replace students who can reason well.<\/p>\n\n\n\n But students who can\u2019t? They\u2019ll be replaced by the first confident chatbot that sounds smarter than they are.<\/p>\n","protected":false},"excerpt":{"rendered":" Last week, I was in a classroom with a group of students that need more AI knowledge to augment what they learned in the regular curriculum. Personal Mission. Not the kind of \u201clecture hall\u201d classroom, but the messy, buzzing kind, laptops open, coffee cups scattered, and a quiet background hum of ChatGPT tabs working overtime. 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