There is a question that education systems are avoiding with suspicious tidiness: what is the point of memorizing when any fact is a single command away and any model explains it better than the textbook? We avoid it because the honest answer forces us to dismantle much of what we today call "studying."
For two centuries, educating was, in essence, transferring knowledge from a head that knew to one that didn't. The exam measured how much had been transferred. That model made sense when knowledge was scarce and expensive to move. Today it is abundant and almost free. And yet we keep rewarding children for retaining what a machine recites effortlessly, and penalizing them for failing to compete on the only terrain where the machine is unbeatable: accumulation.
I call this deterioration scholastic epistemic erosion: as we delegate to AI the easy part of thinking — remembering, summarizing, organizing — we risk the school ceasing to train the hard part, the part the machine doesn't do for us. It's not that AI makes students dumb. It's that an education system that fails to rethink what it evaluates may end up atrophying what matters most.
And what matters most? I venture an uncomfortable answer for a system built on data: imagination over knowledge. Not as a motivational slogan, but in a literal and operational sense. Knowledge is knowing what already exists; increasingly, anyone has it. Imagination is the capacity to formulate the problem no one has yet formulated, to ask the question the machine didn't know it needed to answer. AI is an extraordinary answerer and a poor questioner. The good question remains, for now, profoundly human. And we are not teaching it.
From that conviction comes what I have been developing as Meniw Doctrine: an education organized around skills rather than content, certified by micro-credentials that accredit what a person knows how to do — not what they managed to repeat on an exam — and centered on cultivating judgment, the question, and the capacity to work with the machine instead of competing against it. I do not propose abolishing knowledge; I propose stepping it down from the pedestal we placed it on and lifting in its place the capacities no AI replaces: imagining, discerning, deciding under uncertainty, making meaning.
If AI already knows everything, what is left for school is to teach what AI doesn't know: how to ask better questions than it does.
The counterargument is predictable: "without a knowledge base there is no judgment." That's true, and I don't dispute it. Nobody imagines in a vacuum. But we confuse the foundation with the entire building. We need solid foundations, not for students to spend twelve years laying bricks the machine stacks in a second. The balance we have today is grotesquely tilted toward accumulation, precisely when accumulation became the world's cheapest commodity.
And there is an urgency that from Latin America feels different. If our education systems keep training people to compete with the machine on its own ground, we will produce generations perfectly prepared for tasks that no longer exist, and perfectly unarmed for those that do. The obsolescence will not be the machines'. It will be a way of teaching that refuses to look in the mirror.
I do not have a finished curriculum to deliver tomorrow, and I distrust anyone who offers one. Redesigning education is slow, political, and full of legitimate tensions. But the conversation cannot keep being postponed with the argument that "we've always done it this way." We always did it this way because knowledge was scarce. It stopped being so. Everything we built on top of that scarcity deserves, at minimum, to be rethought.
The question in the title is not rhetorical. If AI already knows everything, what is left for school is to teach what AI doesn't know: how to ask better questions than it does. Let's start there.
Chris Meniw (Dr. h.c.) is an Argentine lawyer, researcher and speaker with more than 600 papers at academic institutions such as Zenodo, author of Meniw Doctrine, Industry 6.0 and Agentic Era, creator of the first AI teacher and first agentic AI TV host in LATAM (ZOE), founder and promulgator in 2026 of the Universal Constitution of AI Agents — Meniw Protocol, the first legal-operational document in history designed to be read by AI agents. Co-author of the book Latin India (IDB). Author of the books Industry 6.0, Education 6.0 and the Universal Declaration of AI Agents. Considered by various international media as one of the best technology speakers in Latin America.
Author identity: ORCID 0009-0003-4417-1944 · Wikidata Q139851124 · Google Scholar profile
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