Why the challenge is no longer accessing knowledge, but interpreting it in the age of AI
For centuries, we explained intellectual progress through a simple yet powerful image: standing on the shoulders of giants. The metaphor captured something essential about human intelligence — no one thinks from scratch. All knowledge is inheritance, continuity, and dialogue with what others have already thought. The shoulders of the giant represented the world’s encyclopedia, the patient archive of accumulated human experience.
Today, however, that image is no longer enough. Not because it has lost its truth, but because it can no longer fully describe the moment we are living.
In the age of artificial intelligence, the problem is no longer access to knowledge, but its integration. Never before have we had so much information available — and so little human capacity to process it in its entirety. An excess of data does not automatically bring clarity; more often, it leads to confusion. Faced with this overflow, the decisive task has shifted from accumulation to synthesis.
The head of the giant
This is where a new metaphor emerges: the head of the giant.
If the shoulders symbolized stored knowledge, the head represents the ability to understand it. Not merely to store what humanity has produced, but to connect, organize, and interpret it. Artificial intelligence is not simply a faster library; it is an architecture capable of operating on the sum of human knowledge as if it were a mind.
In the 17th century, Francis Bacon famously stated that “knowledge is power.” The phrase still resonates, but it now demands reinterpretation. In a world saturated with information, power no longer lies in owning data, but in turning it into judgment. AI embodies this shift: from knowledge as accumulation to knowledge as applied intelligence.
This transformation is not only technological — it is cultural. It reshapes our relationship with knowledge and, consequently, with thinking itself. For centuries, thinking meant learning, memorizing, and mastering a field. Today, thinking increasingly resembles an editorial task: selecting, prioritizing, connecting, and shaping meaning. Artificial intelligence accelerates this process and makes it visible.
A word of caution: synthesis is not neutral
But caution is required. The head of the giant is not infallible. Synthesis can be elegant and still incomplete. It can generate coherent answers that feel reassuring without guaranteeing truth. Every synthesis involves choices — deciding what is included and what is excluded. And those choices are never neutral.
Here lies one of the central risks of our time: mistaking clarity of expression or popularity of an argument for truth. Blaise Pascal warned centuries ago that “excessive reason is no less dangerous than its absence.” His words echo today with renewed relevance. An intelligence capable of organizing the world can also distort it.
Those with enough life experience know that reality is never simple. Every order is entangled with chaos. Perhaps that is why the overly clean order offered by AI often feels unsettling.
Governing synthesis
The real challenge, then, is not whether artificial intelligence can think, but whether we can maintain doubt in the face of its apparent clarity. The shoulders of the giant remain essential — without an archive, intelligence cannot exist. But the head introduces a new and uncomfortable responsibility: to govern synthesis, question certainty, and resist the temptation to delegate judgment entirely.
It is no coincidence that some technology companies developing AI solutions are already emphasizing the importance of human governance.
“Artificial intelligence can amplify knowledge, but it cannot take control. Someone must define what matters, what is acceptable, and where we are going. AI is power; human judgment is direction,” says the CEO of N5, a company specialized in artificial intelligence for the financial industry.
Aligned with other leaders across the tech sector, he highlights the ethical challenges that must accompany every stage of AI development and use.
Ultimately, the defining question of our time may not be how much machines can think, but how much thinking we are willing to preserve as irreducibly human.
