What the official frameworks ask people to know
These frameworks describe expected competencies. None of them provides a course for reaching them. This page says what each one asks people to know, and where this course gives it.
A funder, a head teacher or a ministry often asks the same question: what does The AI Manual rely on? This page answers with public documents, each one opened at its address at the time of writing. It claims to invent nothing: it ties what those documents ask people to know to the precise place where this course gives it.
On this page
An expected competency, not a course
The four frameworks that follow describe competencies: what a person should be able to do when faced with an artificial intelligence system, at what level, at what age or in what job. None of them explains how a model builds its answer, why it makes things up with total confidence, or where its biases come from. That is no failing on their part: describing an expected competency and teaching how to reach it are two different trades. This course does the second, chapter by chapter, and shows it below, framework by framework.
The OECD and European Commission framework
The OECD and the European Commission, with the support of CodeAI, publish and launch this framework on 17 and 18 June 2026 in Brussels, after an open international consultation on a draft from May 2025 that drew more than two thousand contributors. It addresses primary and secondary education, and feeds the innovative domain of the PISA 2029 survey.
It describes four competence areas, nineteen competencies in all, each made of a piece of knowledge, a skill and an attitude: engaging with artificial intelligence, creating with it, managing it, designing it. Its area for managing AI calls for knowing what you choose to hand to a system, and what becomes of it.
What that framework allows anyone to state, this course gives in the chapter what you give it: the four distinct things that happen to a text, an image or a file handed to a service.
The UNESCO framework for students
UNESCO publishes this framework on 8 August 2024, during its Digital Learning Week. It addresses students in school education.
It describes twelve competencies across four dimensions, at three levels of progression: understand, apply, create. Its four dimensions are a human-centred mindset, the ethics of artificial intelligence, its techniques and applications, and the design of artificial intelligence systems. Its dimension on the ethics of AI calls for knowing why a system reproduces imbalances it did not choose.
What that dimension asks for, this course gives in the chapter where the biases come from: a demonstration where you skew the make-up of a corpus yourself, and watch the model give back exactly the skew you set.
The UNESCO framework for teachers
UNESCO publishes this framework on the same day, 8 August 2024: the first global framework of its kind designed for teachers themselves, and not for their students.
It describes fifteen competencies across five dimensions, at three levels: acquire, deepen, create. Its five dimensions are a mindset, the ethics of artificial intelligence, its foundations, its pedagogy, and professional development. Its dimension on a human-centred mindset calls for being able to recognise the situations where a machine’s answer has no place, not only those where it has one.
What that dimension expects, this course gives in the chapter when not to use it: three tests for deciding whether a situation allows anyone to rely on a machine’s answer, and why a detector never proves anything.
A non-European framework: AI4K12
AI4K12 is not a European framework, and that is exactly why it appears here: the work of artificial intelligence literacy belongs to no one continent. The AAAI and the CSTA have been publishing it since 2018, with support from the United States National Science Foundation, and have kept it up to date since. It addresses United States classrooms by grade band, from kindergarten to the final year of high school (K-2, 3-5, 6-8, 9-12 in its own terms).
It describes five big ideas: perception, representation and reasoning, learning, natural interaction, and societal impact. Its big idea of perception is about the way a system captures and represents an image, a sound or a text.
This course turns that question around: how to recognise that an image has been fabricated, not merely perceived. What that framework allows anyone to state, this course gives in the chapter a fabricated image: two images fabricated on the device that opens the page, their spectra side by side, and the limit of the method, since a little noise is enough to wipe it out.
What the frameworks ask for, and where this course gives it
The table keeps one point per framework, and stops at the chapters already published: a row with no real chapter behind it is not written.
| Expected competency | Framework that asks for it | Page of the course that covers it |
|---|---|---|
| Knowing what you choose to hand to a system, and what becomes of it | OECD and European Commission, area for managing AI | What you give it |
| Understanding why a model reproduces the imbalances of its training data | UNESCO, framework for students, dimension on the ethics of AI | Where the biases come from |
| Deciding whether a situation allows anyone to rely on a machine’s answer | UNESCO, framework for teachers, dimension on a human-centred mindset | When not to use it |
| Recognising the clues, and their limits, of an image fabricated by a machine | AI4K12, big idea of perception | A fabricated image |
What is regulatory does not belong to this core
European Union law sets, on top of these frameworks, a separate obligation: its regulation on artificial intelligence requires every provider and every deployer of a system to support the artificial intelligence literacy of their staff, whatever the risk level of the system. That obligation has applied since February 2025.
It has nothing to do with the four frameworks above: a framework describes a competency to be reached, a legal obligation imposes an effort on an organisation, under an authority that can penalise it. The mechanism of a model is the same everywhere: a chapter describing it holds for every language of this course. A legal obligation does not: it holds for one territory and not for another. That is why it is dealt with apart, as a module placed beside this core, never inside this core: see the European obligation.
See also
What this site is, and what it commits to, is described on the about page. Every source of this course, framework by framework and theme by theme, is listed on the credits page.
Sources
- Empowering Learners for the Age of AI (“AILit Framework”), OECD and European Commission, with the support of CodeAI, 2026.
- Empowering Learners for the Age of AI (full report, PDF), OECD Publishing, with the European Commission, 2026.
- AI Competency Framework for Students, UNESCO, 2024.
- AI Competency Framework for Teachers, UNESCO, 2024.
- AI4K12: Five Big Ideas in AI, AAAI and CSTA, funded by the National Science Foundation, 2018.
- Regulation (EU) 2024/1689 (AI Act), consolidated text, Article 4 “AI literacy”, European Union, EUR-Lex, 2024, text consolidated as at 27 July 2026.