International Organizations Collaborate on AI Education Framework

The European Commission and the Organisation for Economic Co-operation and Development (OECD) are partnering with Code.org to develop an open and collaborative learning framework for AI and its use in education (learning with and about AI). The initiative invites everyone to contribute their opinions. Benjamin Ninassi and Ikram Chraibi Kaadoud are involved in this project.

Prologue

Imagine the 1870s. A seemingly monstrous phenomenon emerges: people begin to hear voices of others located dozens of kilometers away. This was terrifying. Was it magic or a curse? It was the advent of the telephone. Since then, we’ve explained to our children how it works (in physics class) and its technological uses (in dedicated courses), including its limitations (like “fake” calls).

Now, fast forward to 2070. Children laugh at the fact that a century earlier, “artificial intelligence” was considered a mysterious family of algorithmic inference mechanisms. Its workings seemed either magical or potentially malevolent. But that was then. In this vision of the future, we have all learned (i) how these algorithms work and (ii) how to learn with the help of such algorithms (learn with and about AI) with discernment and moderation.

Unless, in a far more dystopian future, we have only allowed people to use these tools without understanding (“no need… it works on its own”) or mastering them (“just a few clicks, it’s so easy”). This world (imaginary?!) would be more fractured and terrible to live in than a totalitarian world subjected to ultra-surveillance like George Orwell envisioned. If our daily lives (access to information, choices regarding our decisions), now digital, were in the hands of a few people (for example, “the richest in the world”), our own minds would be poisoned, made vulnerable by ignorance and a lack of critical thinking. Moreover, with the current rate of global warming, in 2070 with a planet at +3°, children probably won’t be laughing much.

Let it not be so.

For several months, a team on both sides of the Atlantic has been making a collective contribution to ensure that our future is the best it can be regarding these AIs that we keep talking about.

Did you say A.I.L.F.? (AI* Learning Framework**)

ailiteracyframework.org

(*) Let’s say “AI,” keeping in mind that these are algorithmic inference tools (plural), no more, no less.
(**) A framework for learning these tools that we call artificial intelligence.

AI literacy represents the technical knowledge, lasting skills, and good attitudes (knowledge, know-how, and soft skills) that allow us to interact with AI, create with such tools, manage and design them, while critically evaluating their benefits, risks, and ethical implications.

It’s as essential as reading, writing, or counting. With several points in common:

These are universal skills for everyone, but with significant cultural variations to respect: everyone must be able to learn AI and use AI to learn, and must be able to become autonomous with respect to AI, but in respect of their diversity.
These are interdisciplinary skills, intended to be integrated into all relevant disciplines, computer science, mathematics, and technologies, as well as the humanities and transversal pedagogical training of students. Many of these skills (critical thinking, computational thinking, problem-solving) are already shared – all the better – the contribution of this framework is to help do it in the context of AI.
These are perennial skills: we are talking about fundamental knowledge, know-how, and soft skills, which will still be relevant during the expected evolution of current tools (just as in computer science we do not learn “Python” (or another language) but algorithms and information coding, relying on such and such formal language that may change over time).
Among the additions to be made to the current version, the environmental impacts of AI, already taken into account, are to be strengthened: the direct environmental impacts of each learning, each inference, each investment in favor of an AI-based solution are already real today, as well as the indirect deleterious environmental impacts of many use cases.

This literacy primarily targets primary and secondary education, but is also open to peri- and extra-curricular activities, and family education.

It is a joint initiative of the European Commission and the Organisation for Economic Co-operation and Development. Code.org and very diverse international experts support its development.

So… concretely?

Discover and give your opinion. Here is, in one page, this framework which aims to be inspiring, rich in resources, without any binding value:

Here: ailiteracyframework.org you have all the presentation elements. There is even a “prompt” (the instruction or question that is asked textually to an AI with a language interface) to question an AI about this AI literacy.

A first version, completed and carefully reviewed, is available for working on specific elements. No mistake! It is obviously intended to evolve and be remodeled, even questioned in depth, depending on the readings and feedback.

So… it’s your turn!

Over the next few months, we are soliciting comments from stakeholders around the world. To participate, visit www.teachai.org/ailiteracy/review. The final version of the framework will be published in 2026, accompanied by examples of AI mastery in curricula, assessment, and professional development.

Thierry Viéville, Inria researcher.

Ok… 1,2,3: how do I get started now?

– With the ClassCode I.A.I. training, you can learn the basics of AI without any technical prerequisites, to understand how it works:

pixees.fr/classcode-v2/iai

Resource freely usable and reusable.

– Train teachers on the context, use, relevance, and challenges of educational resources using artificial intelligence in an educational setting:

tinyl.co/3PMs

With free online training and reusable multilingual resources.

– To go further:

www.elementsofai.com

is a training course updated this year that allows you to really learn about the foundations and uses of AI.

– And just as important: training on the environmental impacts of digital technology, including AI:

www.fun-mooc.fr/fr/cours/impacts-environnementaux-du-numerique

At a time when ecological transition often rhymes with digital transition, what are the real environmental impacts of digital technology? How can we start acting now for a more responsible and sustainable digital world?

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