Published on 13 July 2026 in Núvol magazine.
At the beginning of the year, during an expedition through West Africa, I visited a secondary school in Bissorã, Guinea-Bissau. Its director, Djoncon Camara, welcomed me with an impressively calm presence. He had worked with Mother Teresa in the 1990s and spoke of education as something that is not only conceived in the mind, but also built with one’s hands. As we walked across the school grounds, an open space in the middle of the tropical savannah, I noticed in the distance a strange arrangement of objects laid out on the ground, covering an area almost the size of a football pitch. When we approached, Djoncon explained that the students and teachers were making mud bricks themselves, using moulds they had also built, to construct a future school building.
That image remains vivid in my mind: hundreds of pieces of mud arranged in rows, slowly drying in the sun. The students and teachers had dug up the earth, mixed it with water until they found the right consistency, pressed it into the moulds, carefully removed each brick and left it to rest until it hardened. And the people carrying out this work were the same people who would later construct the building. No stage between the raw material and the wall had been omitted. Every brick contained the hands that had made it, and the wall would contain all the bricks. The final result incorporated the entire process that had made it possible, with students and teachers working side by side.
What becomes evident in this form of artisanal construction can also be recognised in any intellectual process, whether at a university, a school or even within a company: the process is not merely a preliminary stage leading to the result. The process is already part of the result. It is a dynamic of creation in which thought, material, effort, error, time and understanding gradually give substance to what ultimately appears as a finished product. In this sense, the result is also a phenomenon of emergent cooperation. It does not suddenly appear at the end, but gradually takes shape along the way through everything that constitutes it and makes it possible.
In our time, it is almost inevitable that artificial intelligence will form part of intellectual development processes. The challenge arises, however, when it ceases to be part of the journey and becomes merely a shortcut to the result. At universities and secondary schools, we increasingly discuss the risk that AI may be used only to produce a good final “product”, rather than necessarily to improve learning. We must also ask ourselves honestly whether what we continue to assess is primarily the student’s own performance or, increasingly, their ability to manage a tool.
When the objective we communicate is to obtain the highest possible grade, students will seek that shortcut as efficiently as possible. This is beginning to call into question the very purpose of awarding individual grades based on performance. In the assignments I have received during recent semesters at the university, I have often observed that the results are formally very correct, yet remarkably similar in the way they are expressed and in how they reach their conclusions: occasionally profound and innovative, but more often generic.
Young people have always been the driving force behind innovation and unconventional thought. We cannot afford to lose that. Yet it becomes even more troubling when AI is used only to reach the result and the learning process itself, the living core of any educational experience, is omitted. There may be something more problematic still: if we continue along this path, we may gradually lose both the habit and the process of thinking for ourselves. This habit is not merely an academic competence; it is also a condition of freedom and democratic life.
A learning process requires us to enter into complexity. We need to have doubted, tested examples, abandoned certain paths and encountered limits. We need to have asked ourselves what is essential and what is merely ornament.This is the true meaning of didactic simplification: moving through complexity until we arrive at a form of simplicity that can be understood. The kind of effective simplification we need in classrooms does not arise from reducing complex subjects until they lose their substance. It comes from understanding them well enough not to betray them. Afterwards, everything may appear simple to others, but only because it was difficult beforehand.
This learning process does not exclude AI, which can perfectly well form part of it. However, when the process disappears, AI may still allow us to produce a sufficiently correct final product—perhaps even one that is well written, well organised and formally convincing. When we have not travelled the entire path, our relationship with the result becomes weaker. We may be able to use it, but we cannot always fully inhabit or transform it, because we have not understood its essence. And yet we tend to describe what we observe among students as the problem we are facing. Perhaps, in reality, it is only a symptom. We should therefore have the courage to examine the issue more deeply.
What happens when a teacher attempts to shorten or accelerate the preparation of a class through AI? What happens when, instead of genuinely engaging with the subject, they merely generate content from the reading list, prepare a set of slides or a worksheet and enter the classroom with a lesson that is formally correct, but lacking in depth and passion? Everything may appear to be in order. There are objectives, activities and materials. But something more difficult to measure is missing: the teacher’s resonance with the subject—their own perspective, accompanied by a certain emotion or even passion, which makes all the difference.
Students value a teacher’s passion for a subject more than we may realise, and they perceive it immediately. When they see someone who has truly made an effort, who has not taken the shortest route and who genuinely cares about what they are explaining, they do not merely learn the course content. They also learn a way of approaching knowledge. This example inspires more than any particular piece of content. The long path of genuinely engaging in the exercise of thinking also reveals when we are mistaken. It exposes what we have not sufficiently understood. It shows us the limits of our own thinking and forces us to pause. And very often, it opens us to dialogue with others, allowing us to learn from someone with a different perspective or greater experience.
When we use AI superficially, a problem is resolved from the outset and we arrive at the result very directly. Everything may sound correct and polished. But the problem is not that the result is bad. The problem is that it is very often sufficiently acceptable: superficial, but correct. That is where the danger lies. A bad answer forces us to react; a mediocre answer may leave us passive. It is a kind of silent amnesia: we do not perceive what we have ceased to think about because no trace of it remains.
It takes experience and dedication to recognise that a result has fallen short, and young people are not always yet able to see this. AI, like any tool, is valuable when it expands our thinking and reveals new possibilities. The question is how to recognise the moment when a tool stops helping us to think and begins to spare us from thinking for ourselves.
A society that merely consumes results may gradually lose the ability to understand itself. Because not every shortcut brings us closer to the place we truly want to reach.
