Thinking Beyond Knowledge
Why AI Takes Over Knowledge – And Gives Us Thinking Back
Few areas lagged behind in digitalization as long as education. And yet it was here, of all places, that artificial intelligence first sparked not just enthusiasm but critique.
Not from within, but because many students quickly realized what this technology could do.
Not out of curiosity. But because they had already internalized what really counts: Efficiency. Optimization. Results.
I was a bad student.
The system had clear expectations, and I didn’t really meet them.
“Smart, but lazy,” I heard often. Or rather: my parents did. Regularly, from parent-teacher meetings. The school system warned I was wasting potential, and that it would haunt me for life.
I wasn’t slow or too fast. I was selective. Whatever interested me got my full attention. The rest passed me by.
I had time, and it wasn’t until the last semester before graduation that I finally flipped the switch. The “ignition” came late, but it came.
That period coincided with the time when Germany was called “the sick man of Europe1.” We kept hearing we had to perform more, be more flexible, in a system that wasn’t flexible at all.
Only at our graduation ceremony did the parents’ speaker break that narrative. She rejected it, and told us we’d do well to believe in ourselves.
I remember that it felt good, and today I know:
She was absolutely right.
Education as a Mirror of a System
Education was never just a personal process. It has always mirrored societal expectations and economic goals.
One example of this is the Bologna process, which has made higher education more economically oriented, viewing education increasingly as a productivity unit.
The focus shifts: It’s less about individual development and more about marketability.
But the Bologna process is only a visible expression of a larger problem.
The education system still carries remnants from the 19th century2, when it aimed to prepare people for industrial work. These old structures still hold on to a performance-oriented mindset, which leaves little room for creativity and individual growth.
The system is a reflection of the economic mindset that rewards efficiency and adaptability.
The questions remain: Do we manifest these expectations, thereby reinforcing the structural problems of the economy in future generations?
And: What happens to students' autonomy when the educational path is only focused on the usability of knowledge?
From Conformity to Maturity
Educational systems have always demanded that students adapt. To a structure shaped by efficiency and social expectations.
This adaptation often leaves little room for self-determination, reducing the learner to a mere product of the system. But true maturity does not arise from conformity. It grows through selectivity. The ability to decide for oneself what matters, what learning truly means, and what one’s own path through the system could be.
Maturity means not just reacting, but acting and reflecting.
Selectivity empowers learners to guide their own process, without being completely shaped by external demands.
Today, technology could give this selectivity a new meaning, opening new paths for autonomy and self-determination.
But the central question remains: How can we trust technology if the true goal of education is still to enable self-directed reflection?
Between Assistance and Control
This question touches on the core of a current debate: What role should technology play in the educational process, and where does the loss of pedagogical responsibility begin?
On the one hand, artificial intelligence offers new possibilities:
Curriculum content can be tailored more individually, learning progress can be captured more precisely, repetitions can be offered more effectively.
Teachers could be relieved by digital assistants, not replaced, but supported.
And for students who have previously fallen through the cracks, new pathways for access and participation could open up.
From this perspective, AI wouldn’t contradict autonomy. It would be a tool that helps strengthen it.
But on the other hand, with each new interface, the control over the educational process shifts.
When digital systems increasingly decide what, how, and to what depth something should be learned, not only pedagogical freedom is up for debate, but also the democratic mandate of schools themselves.
Who controls the algorithms?
Who curates the content?
Who ensures that support doesn’t turn into profiling, or quiet disciplining?
What starts as a technical aid can quickly become a structural influence. Education is no longer defined in curricula and negotiated in classrooms, but in data centers, guidelines, and business models.
World-readiness – Education in the Post-Knowledge Age
As AI becomes infrastructure, a more fundamental question arises: What is it educating us for, and what exactly are we preparing for?
AI can present content. Organize relationships.
Recognize patterns. It can check, simulate, formulate.
But what it cannot do: Ask questions that haven’t been asked yet.
The ability to orient oneself, even when nothing is certain.
The willingness to take responsibility, even when knowledge is incomplete.
The desire to think, even without a clear outcome.
Perhaps what’s needed today isn’t a new tool.
But a new concept.
World-readiness.
The term has been used somewhat marginally so far, sometimes as a system-critical measure for the sustainability of our way of life, sometimes as a philosophical impulse for responsible engagement in the world3.
But it often remains abstract, as a programmatic buzzword.
Maybe it’s time to make it more concrete: Not states. Not “humanity.”
But each individual. People need to be world-ready.
People who can navigate — without a map.
People who can handle contradiction without losing themselves.
People who can think before they act — even when no one asks them.
Education would then no longer be training for exams, but a training ground for world-readiness.
No new material. Just a new mindset.
No new discipline. Just a new focus.
Not: What do you know? But: What do you do with what you (don’t) know?
Rethinking Education
Maybe artificial intelligence could not just support schools, but challenge them. And in doing so, save them.
Not as another tool for efficiency, but as a disruption. A prompt to ask: What’s it really about?
When what was once considered the core of education — repetition, application, reproduction — is now effortlessly handled by machines, there is not less left, but more: The question of meaning. Of attitude. Of judgment.
Perhaps real education begins where AI hits its limit:
When it’s no longer about what you know, but what you do with it.
When it’s no longer about how well you reproduce, but how clearly you ask.
When learning no longer means reaching a result, but developing a thought.
Then, school wouldn’t be just the waiting room for the workplace, but a space for autonomy.
Not sorting, but empowering.
Not control, but responsibility.
And maybe this vision doesn’t stop at the school door. Because the very same technology that is discussed in the classroom today could soon work somewhere else, in the living room, in the library, in retirement.
One and the same language model, with a different framework, different language, different task.
No longer as a tool of the institution, but as a partner of learning.
Anytime. For everyone.
Maybe that would be the greatest progress: That education no longer ends, because access is no longer limited.
The question of who pays for it remains important. But perhaps we need to ask it differently: Not as a cost point in the education budget, but as a strategic investment.
Because the people who learn to work with technology like AI — critically, creatively, independently — are not only better prepared for their own future. They are also exactly what an economy needs, one that no longer knows what tomorrow will bring.
What begins in school also concerns the economy. And what succeeds there could become the European model: An AI that doesn’t dominate, but serves.
A technology that doesn’t set the pace, but helps people find their own. Then, education would no longer be just a matter for the states4, but European future policy.
We Don’t Have to Start from Scratch
When we think about how education should respond to a world with AI today, we often act as if there is no compass. But that’s not entirely true. There are disciplines that have been teaching exactly what’s needed now for decades: Thinking in uncertainty. Working with open questions. Structuring without a ready-made solution.
Design is just one example. I’ve personally taught UX design at a university. Not tools, but approaches. And I’ve seen that many of these ways of thinking are already here. Just not where the main curricula are developed.
In design, you don’t teach to simply “make things look nice”, but to create something that doesn’t yet exist. To figure out what’s a symptom and what’s the cause before searching for solutions.
Design education, deeply rooted in Germany, from Bauhaus to the Ulm School of Design5, has developed methods to approach problems instead of rushing to answer them. It teaches judgment, context understanding, and the ability to tolerate ambiguity. All skills that are sorely missing in today’s educational debates, and are urgently needed in the AI-driven world.
From Weakness to Structure
The education system has long been criticized, too rigid, too old, too narrow. Many have struggled with it, many have failed because of it.
But perhaps now we are entering a moment where a new way can emerge.
When we rethink education, we’re not just creating alternative paths, we’re also correcting an image that has long been taken for granted.
I was considered smart but lazy.
For a long time, that was seen as a flaw, in a system that only recognized what could be measured.
Years after school. I had completed vocational training, studied, and was well-established in my career, I read a sentence that sparked memories and made me smile:
"Those who are smart and lazy at the same time qualify for the highest leadership roles, because they possess the mental clarity and nerve strength to make tough decisions."
It was said by Kurt von Hammerstein-Equord, someone who came from a world of norms, who knew what conformity meant and what it could achieve. And he saw a place for those who are both smart and lazy.
The idea of a "leadership role" was flattering, but what really touched me was something else: That laziness doesn’t have to mean inactivity, but can be a drive: To question processes, to avoid detours, to direct energy where it can truly make an impact.
Maybe I was never lazy. Maybe I was just early on the search for meaning.
And perhaps I was simply lucky to eventually meet paths and people who showed me how something valuable could emerge from this.
Today, I try to understand structures, and to shape them so that others can work better within them, so their hard work doesn’t dissipate in contradictions.
Germany was described as the “sick man of Europe” in the early 2000s, in the context of high unemployment and pressure for economic reforms.
The idea of industrial standardization of education has shaped many school systems since the Prussian era of reform. With a focus on discipline, functionality, and reproducibility.
The concept of “world-readiness” has been discussed by educational researchers such as Annedore Prengel and philosophers like Peter Sloterdijk. The underlying idea of “being-in-the-world” goes back to Hannah Arendt, who saw education as a prerequisite for responsible action in a shared world.
In Germany, education is a matter for the federal states ("Bundesländer"), with each state having its own educational policies and regulations.
The Bauhaus (1919–1933) and the HfG Ulm (1953–1968) significantly shaped the relationship between design, society, and learning processes.