{"id":2063698,"date":"2026-06-22T14:00:35","date_gmt":"2026-06-22T12:00:35","guid":{"rendered":"https:\/\/www.luxsure.fr\/2026\/06\/22\/preparing-for-the-unknown-universities-confront-ai-which-they-can-no-longer-ban\/"},"modified":"2026-06-22T14:02:36","modified_gmt":"2026-06-22T12:02:36","slug":"preparing-for-the-unknown-universities-confront-ai-which-they-can-no-longer-ban","status":"publish","type":"post","link":"https:\/\/www.luxsure.fr\/en\/2026\/06\/22\/preparing-for-the-unknown-universities-confront-ai-which-they-can-no-longer-ban\/","title":{"rendered":"Preparing for the Unknown: Universities Confront AI, Which They Can No Longer Ban"},"content":{"rendered":"\n

The university has never merely imparted knowledge. It has facilitated a gradual initiation: learning to reason, to question, to make connections, and to develop a way of thinking that is not merely the reproduction of content. The widespread advent of artificial intelligence does not undermine this mission. It makes it more visible, more urgent, and perhaps more difficult. <\/p>\n\n

The paradox is now well known: students are already using AI, often even before entering higher education. In a major survey conducted in higher education and research, 92% of students reported already using generative artificial intelligence. That figure has undoubtedly risen even further. But usage does not equate to mastery. Some use ChatGPT, Claude, Mistral, or other models without always knowing what generative AI actually is, what it produces, what it doesn\u2019t know, or what it sometimes invents. <\/p>\n\n

This is where the real divide lies. Not between students who use AI and those who don\u2019t, but between those who know how to use it as a tool for their work and those who simply consume it as a ready-made solution. <\/p>\n\n

The Illusion of Understanding<\/h2>\n\n

In lecture halls, this scene has become a familiar one. A student arrives in class with a summary already prepared by an agent. The material has been absorbed, condensed, and rephrased. The knowledge is accessible even before the professor speaks. But understanding is not the same as summarizing. And learning is not the same as getting an answer. <\/p>\n\n

This is one of the most insightful points raised by the winning students of the Global Partnership on AI\u2019s Grand Challenge, organized by Inria. One of the projects presented, T-TWICE\u2014short for \u201cThink Twice\u201d\u2014specifically tackles this illusion of understanding. The principle is simple: an AI tutor that doesn\u2019t give the answer but forces the student to articulate their reasoning, identifies where they\u2019re getting stuck, and then guides them through a series of questions until they reach the solution. <\/p>\n\n

The issue is not merely educational; it is almost cultural. At a time when AI can provide an answer in a matter of seconds, universities must restore the value of the process. What matters is no longer just the result, but the ability to explain why we arrive at that result. <\/p>\n\n

Moving from AI Fonts to AI Grammar<\/h2>\n\n

The initial response of many institutions was defensive: to ban, detect, and punish. This is understandable, but insufficient. An entire generation is already using these tools to write, search, organize, translate, code, and navigate. Pretending that this usage could disappear amounts to fostering collective hypocrisy. <\/p>\n\n

The WARP project, presented by Indian students, proposes a different approach: no longer treating students as suspects, but as partners. When an assignment is turned in, the student explains how they used AI, how they verified the information, and whether the sources they used are authentic. Using AI is not a violation. Concealing its use is. <\/p>\n\n

This shift is essential. Higher education cannot continue to assess students as if AI did not exist. It must learn to evaluate the quality of its use: the relevance of prompts, fact-checking, critical thinking, and intellectual responsibility. <\/p>\n\n

Guidance as an Enhanced Public Service<\/h2>\n\n

Another project, Orientei, tackles a more political issue: career guidance. Today, a young person can share their aspirations, doubts, and educational path with a generic AI system, one that is often designed for other educational systems, other degrees, and other job markets. In contrast, Parcoursup profiles and institutional resources sometimes remain too static. <\/p>\n\n

Orientei offers a public, free platform based on official French data sources: Parcoursup, Onisep, and France Travail. The goal is not to replace the guidance counselor, but to prepare for the in-person meeting. The AI welcomes users, organizes their questions, and explores possible paths. The counselor then steps in with a clearer foundation, using a summary validated by the student. <\/p>\n\n

This statement says a lot about what a well-designed AI system could look like in higher education: not a replacement for humans, but a way to free up human resources so they can focus on where they are most valuable.<\/p>\n\n

The New Common Core<\/h2>\n\n

The proposal for the AI Certificate, developed as part of France 2030 and tested with approximately 10,000 people in Paris-Saclay, follows this same logic. The goal is not to train everyone to become a specialist, but to provide everyone with a set of intellectual guidelines: understanding what an algorithm, a model, data, machine learning, bias, personal data, and environmental impact are. <\/p>\n\n

The comparison with traffic laws is apt. We don\u2019t expect every citizen to become an automotive engineer in order to drive, but we do require them to know the rules, the risks, and their basic responsibilities. AI should be held to the same standard of civic responsibility. <\/p>\n\n

Universities must therefore provide education both with AI and without it. Knowing how to delegate is valuable only if one is still able to judge what is being delegated. <\/p>\n\n

Training the Trainers<\/h2>\n\n

Perhaps the most sensitive issue remains that of teachers. Students are progressing quickly, often in a disorganized manner. Teachers are experimenting, but without a common approach. Yet educational reform cannot rely solely on isolated initiatives. <\/p>\n\n

Training teachers is becoming a strategic priority\u2014not to ask them to adopt all available tools, but to enable them to redesign their courses: Which exercises remain relevant? Which assessments should become oral, context-based, and formative? How can we measure reasoning rather than just the final product? How can we involve students in redesigning these formats? <\/p>\n\n

Perhaps the most important point made during the masterclass was this: students should not merely be users of educational AI. They must become co-architects of its applications. <\/p>\n\n

The university\u2019s role is not to train students for a specific profession that may no longer exist in the same form five years from now. Instead, it must cultivate a more rare skill: learning how to learn alongside machines that respond quickly but do not always understand what they are saying. <\/p>\n\n

This is less a crisis in education than a return to its core. The university of tomorrow will not be the one that has added AI to its courses. It will be the one that has understood that, in a world saturated with answers, its mission is to teach students how to ask good questions. <\/p>\n\n

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