University and school education have never been immune to the major transformations sweeping through society, but in recent years they have found themselves at the heart of three successive waves: the dot-com bubble at the beginning of the millennium, the COVID-19 pandemic at the beginning of the 2020s, and now the wave of artificial intelligence. Each time, the technological solution is presented as the savior, and promises, funding, and expectations are inflated to the point of excess. Then comes the moment of reckoning, revealing that the problem was not purely technical, but primarily human, institutional and cultural.

 

When the software and internet bubble burst in 2000, the network did not disappear; rather, the illusions faded, and the infrastructure remained. And when the COVID-19 pandemic swept the world, it seemed for a moment that university education would be completely transformed into digital learning, and that lecture halls would be permanently replaced by screens. Universities closed their doors, lectures moved online, and digital tools successfully bridged an emergency gap, preventing a potentially catastrophic knowledge gap for an entire generation of students. But what initially appeared to be a permanent historical shift later proved to be a temporary response to an exceptional circumstance, and much of what was attributed to an "educational revolution" was, in reality, media and psychological amplification of a moment of global fear that held humanity's breath.

 

In this sense, the COVID-19 pandemic was not a health bubble, but a cognitive one: a moment when the media, politics, and economics amplified the impact of technology to such an extent that everything seemed to be transferable to a screen without loss. As the pandemic subsided, the gaps emerged: weakened interaction, eroded motivation, unequal opportunities among students, professorial burnout, and a decline in the depth of knowledge in many areas. Digital tools succeeded in preventing collapse, but they did not succeed in building a better educational system in and of themselves.

 

Today, the same pattern is repeating itself with artificial intelligence, but in a more radical form. It's no longer just about platforms for broadcasting lectures or managing classes; it's about systems that claim to be able to teach, assess, explain, correct, and even foster academic creativity on behalf of individuals. This transformation is being presented in universities, much like e-learning was presented during the COVID-19 pandemic: as an indispensable historical necessity and a qualitative leap that will rescue education from its structural crises.

 

However, this discourse masks a dangerous confusion between the means and the end. The university is not a degree factory or an information production line, but rather a space for cultivating critical thinking and building the capacity for questioning, reflection, synthesis, and dissent. These functions are not reduced to the mere transmission of content or the speed of access to it, but rather to the nature of the relationship built between the student and knowledge, between the student and their professor, and between the student and their own intellectual self.

 

Artificial intelligence, like the educational tools used during the COVID-19 pandemic, can fill gaps: providing additional explanations, translations, summaries, training, simulations, and faster access to resources. However, it cannot, by its very nature, replace the educational experience itself, because this experience is not merely the consumption of knowledge, but rather engagement with it, critical thinking about it, and its reformulation. The danger lies in the university, under the pressure of the market, competition, and cost, becoming an institution that relies on artificial intelligence to reduce staff, accelerate assessment, standardize curricula, and transform education into a digital service, thereby slowly and silently losing its essence.

 

Even more dangerous is that knowledge itself may enter a closed loop of repetition. If students write with the help of artificial intelligence, professors teach with the help of artificial intelligence, and research is corrected with the help of artificial intelligence, then knowledge begins to feed on its own outputs, not on new human experience. Here, we are not dealing with education, but with the recycling of ready-made linguistic patterns and concepts, expanding quantitatively while diminishing qualitatively.

 

Furthermore, the digital civilization, despite its apparent power, is fragile in its memory. What is produced today on university platforms and websites may not survive in two decades if systems change, companies close, or servers fail. Ironically, thousand-year-old manuscripts are still being read, while ten-year-old digital research may vanish without a trace. University education, as the critical memory of society, cannot build its future on media that do not guarantee the permanence of its impact.

 

At its core, what we are experiencing is not a technological crisis, but a crisis of perception. We keep repeating the same pattern: we exaggerate the power of a tool when it appears, we pin our hopes on it for salvation, we use it to bridge a real gap, and then we discover that the gap was deeper than the tool itself, and that the problem lay in the structure of the system, not in the absence of technology. This happened with the internet, with e-learning during the COVID-19 pandemic, and it is happening now with artificial intelligence.

 

The university faces a crucial choice: either to treat artificial intelligence as it treated the tools of the pandemic—as a temporary relief measure, followed by a return to thinking about the essence of the educational process—or to continue down the path of transforming education into a fast, automated product, gaining efficiency but losing meaning. Artificial intelligence can be a catalyst for improving education if it is placed at the service of a thoughtful professor, a questioning student, and an institution that views education as a human endeavor, not an industrial one. Conversely, it can be a tool for draining education of its essence if used to compensate for institutional deficiencies rather than rectify them, and to beautify the crisis rather than confront it.

 

Just as the COVID-19 pandemic held the world's breath for a moment, then subsided, leaving questions unanswered, the artificial intelligence bubble may hold universities' breath today, only to subside, leaving the same question: What do we want from education? If this question is not clearly posed, every new tool, no matter how advanced, will be nothing more than another layer of paint on a wall that is cracking from within.

 

Hasan Dajah - Professor of Strategic Studies at Al-Hussein Bin Talal University