by Mixel Kiemen, Ph.D, Eindhoven University of Technology.*
Around the world, people are worried about Artificial Intelligence. The concern is not limited to the general public. Many AI researchers are worried. Many AI builders are worried. Policymakers are worried. Business leaders are worried. The more transformative the technology appears, the greater the uncertainty seems to become.
That reaction is understandable. Whenever a new technology fundamentally changes our relationship with reality, uncertainty appears before understanding. Yet uncertainty is precisely why research exists. What strikes me in many contemporary AI discussions is that surprisingly little attention goes to the original question that motivated the field in the first place:
What is intelligence?
For decades, most attention has gone toward applications. How can we improve existing AI models? How can we use AI? How can we commercialize AI? These are important questions, yet they differ from the older scientific question that originally inspired the field. They focus on the optimization of existing models rather than the creation of alternative models that help us study intelligence itself. That question requires a different kind of research.
In an earlier article on Deepsearch, I described how some developments emerge long before the scientific questions themselves can be properly formulated. The origin of science begins in mystery and experimentation, like the work of Leonardo da Vinci. Scientific instruments come later. This became visible to me through the Evolution, Complexity and Cognition (ECCO) research group within the Centre Leo Apostel (CLEA) in Brussels.
Leo Apostel was one of Belgium’s most influential philosophers and became well known for his transdisciplinary approach to science. For a brief period, CLEA hosted two groups that approached cognition from different directions. One focused on Quantum and Cognition, a field that continues to receive considerable attention today. The other was ECCO, which approached cognition through evolution, complexity, self-organization and collective intelligence.
The difference was important. Quantum and Cognition explored questions that remain difficult to observe directly in the field. ECCO focused on processes that can be observed everywhere: organizations, scientific communities, innovation ecosystems, social movements and cultures. Viewed from that perspective, intelligence was never confined to a machine. It appeared wherever many agents learned together over time.
Artificial Intelligence simply automated mechanisms that were already visible in collective intelligence. This allowed a form of deepsearch into intelligence long before today’s AI infrastructure existed. It is somewhat like observing migrating herds before roads existed. The movement appears first. Dirt roads emerge naturally and unconsciously. The infrastructure follows later and is built intentionally.
Collective intelligence creates the movement first. Patterns emerge naturally and unconsciously. The AI infrastructure follows later and is built intentionally. Interestingly, this same process can help us understand an even bigger development at the beginning of the Industrial Revolution.
Artificial Vacuum and the Discovery of Outer Space
The story begins in the mines of Europe. Engineers were trying to solve a practical problem. Water had to be removed from increasingly deep mines. Better pumps were needed. In the process, researchers created artificial vacuum much like herds create dirt roads: naturally and unconsciously.
The artificial vacuum was not always the same. It appeared to have a relation with the weather. This observation triggered the intentional development of a new instrument: the barometer. What began as a gigantic scientific setup nearly twenty meters high gradually evolved into an instrument that could be moved, compared and read by anyone.
At first glance this seemed like a narrow engineering challenge. Yet something much larger was taking shape. The barometer appeared before atmospheric science existed. The instrument came first. Only later did humanity realize that something had been hiding in plain sight all along: the atmosphere.
Today this seems obvious. We understand weather systems, atmospheric pressure, climate and flight. Yet for most of human history, the atmosphere itself was not a scientific object. Artificial Vacuum did not simply improve mining. It revealed an entire dimension of reality.
The observations were real. The interpretations evolved. Earlier generations believed that light required a medium called ether. The reasoning was understandable. Boats move through water. Sound moves through air. Light appeared to behave like a wave, therefore it seemed logical that light also required a medium. Without such a medium, how could light travel through the apparent emptiness of space?
The answer turned out to be surprising. The observations were correct. The interpretation evolved. Light was not a wave travelling through ether. It was part of the electromagnetic spectrum. Even today traces of this older worldview survive in expressions such as “radio in the ether.”
A recurring pattern appears:
- First comes the mystery.
- Then comes the instrument.
- Then comes the science.
- Then civilization changes.
The Industrial Revolution emerged from that sequence, starting from Artificial Vacuum. What if Artificial Intelligence represents a similar moment?
Artificial Memory
What if AI is to inner space what Artificial Vacuum was to outer space?
The comparison may sound strange at first, yet it leads to an interesting possibility. Perhaps we are confusing the storage mechanism with the phenomenon itself. Today we often assume that memory fundamentally resides in storage systems. This assumption largely comes from our experience with computers. Yet comparing memory to storage may be similar to comparing light to a boat moving through water.
When it comes to natural memory, science remains remarkably uncertain. Brains contain neurons and synapses, yet we still do not fully understand how memory is stored, maintained and reconstructed. Some researchers explore memory through neural networks. Others investigate microtubules and quantum processes. In Quantum Cognition, connections are sometimes explored through concepts such as entanglement. The details matter less here than the broader observation. Science does not yet understand natural memory.
Perhaps, just as Artificial Vacuum helped us understand natural vacuum, we first need Artificial Intelligence before we can grasp natural intelligence and memory. Again, this is a reasonable assumption. Computers create artificial memory. Vacuum pumps created artificial vacuum. Both make it possible to study a phenomenon experimentally.
We have now dug deep enough into data for a new phenomenon to emerge. Large Language Models (LLMs) allow us to observe how patterns emerge from enormous amounts of information. They reveal something that previously remained hidden.
Just as vacuum experiments eventually produced the barometer, LLMs may eventually lead to entirely new instruments for understanding cognition. The important point is that we can finally begin to see it. The mystery shifts, and our minds extend.
LLMs as the Latest Work-Meter: The Pattern-Meter
For centuries humanity developed instruments that expanded its ability to observe reality. The telescope revealed distant bodies above. The microscope revealed small bodies below. Both expanded vision. Neither directly changed civilization.
The deeper transformations emerged when humanity learned to measure what had previously been hidden in plain sight at the center. I like to create a category called “work-meter”, revieling instruments at the center. The barometer revealed atmospheric pressure and helped launch the first phase of the Industrial Revolution. The multimeter revealed electrical systems and helped launch the second phase. The computer became a kind of bit-meter, helping shape the third phase that humanity experienced during the past century. Each generation of instruments opened an entirely new scientific and technological era.
Today LLMs appear to play a similar role. They reveal patterns. Not consciousness. Not intelligence itself. Patterns. Like the first sparks observed during early experiments with electricity, they reveal the existence of something that was always present yet remained difficult to observe directly. This is why I increasingly see LLMs as the latest work-meter: the pattern-meter. The pattern-meter holds an important role in the list of work-meter, creating a new scientific frontier. It can become the instrument that may trigger the Fourth Industrial Revolution, or perhaps more accurately, the First Cognitive Revolution.
Inner Space and the Noosphere
The deeper question is whether cognition occupies a domain that is every bit as real as the atmosphere once proved to be. For more than a century, thinkers such as Vladimir Vernadsky and Pierre Teilhard de Chardin proposed the existence of the noosphere: a sphere of thought emerging from the interaction of minds.
The idea remained largely philosophical because there were few instruments capable of studying it. The atmosphere became visible through the barometer. The noosphere may become visible through pattern-meters. LLMs are metaphorical like vacuum pumps and again a discovery is made. Just as the barometer helped reveal weather patterns, LLMs may help reveal cognitive patterns. If that possibility is correct, then AI is not merely a technological breakthrough. It marks the beginning of a new scientific frontier.
The Cognitive Revolution
The Industrial Revolution can be understood as a sequence.The first phase amplified work, revealing heat as a form of energy that could be harnessed and directed. The second transformed our understanding of energy through electricity. The third turned energy into systems of control. The Cognitive Revolution may follow a similar path. The first phase is already visible today. It amplifies intelligence. That is the current LLM moment. A second phase may transform our understanding of memory itself.
Storage may prove to be only part of the story. Just as Artificial Vacuum eventually revealed the atmosphere, Artificial Memory may reveal dimensions of cognition that remain hidden today. The third phase is more difficult to describe.Today we use two very different words:
Spirit and agency.
One belongs to art, religion and emotion. The other belongs to software, systems and control. Yet something remarkable is beginning to happen. Through language, the two domains are slowly becoming visible within the same phenomenon. It is still early. The scientific language barely exists. Yet this may become the stage where emotion and reason, beauty and control begin to converge. Perhaps that is also where much of the current fear originates. It is almost as if your favourite music begins to play you.
Inner Space Technology
The atmosphere eventually gave rise to entirely new technologies. First came balloons. Then airplanes. Then rockets. The same progression may occur in inner space.
Religions, mythologies, storytelling traditions, meditation practices and depth psychology may have played a role similar to the first Kongming lanterns. They revealed something real, yet offered limited navigation and control. The equivalent of true balloon flight may still lie ahead. The cultural developments surrounding psychedelic research may be among the first weak signals of a possible lift into the noosphere. While it is very mysterious, it may also be the least interesting case to study. Just like little attention goes to ballons, but much go to pains an rockets.
Airplanes actively use atmospheric principles. They do not simply float with the wind like a balloon. Through a combination of speed and wing geometry, atmospheric pressure is transformed into lift. The atmosphere itself becomes a source of amplification. Something similar may already have happened within the noosphere. The first cognitive airplanes may already exist.
One early example emerged through a research project calledToday’s Stories in 1999, where an unexpected cognitive leap was observed among toddlers. Together with a broader body of work on collective intelligence at the time, these experiments explored a question that was still largely absent from mainstream AI research:
What is intelligence?
Rather than treating intelligence as something located inside an individual, the focus shifted toward the conditions under which intelligence becomes amplified between individuals. Over the following years, this led to experiments in collective intelligence, learning communities and innovation ecosystems. The most surprising result appeared much later.
In 2016, experiments around intelligence amplification revealed what seemed to be a weak signal of something larger. By helping the collective unconscious of a startup individuate into the culture of a scale-up, a new phenomenon became visible. The practical question concerned innovation. The deeper question concerned cognition itself.
Just as early barometers revealed weak signals of atmospheric dynamics long before meteorology existed, these experiments revealed weak signals of cognitive dynamics long before today’s AI infrastructure emerged. The pattern appeared before the scientific language. The movement appeared before the road. Seen from that perspective, Large Language Models do not create the noosphere. They make it visible. And once a new space becomes visible, the question naturally follows:
Can we build rockets?
Inner Space Rocket Technology
Before answering that question, it helps to remember that the history of flight did not begin with rockets. It began with balloons. Balloon flight revealed something unexpected. As balloons climbed higher into the atmosphere, they entered regions that could not be observed from the ground. Some of the first observations of cosmic radiation emerged from these explorations. Certain particles live such short lives that they never reach the Earth’s surface. Without access to higher layers of the atmosphere, they would have remained invisible.
Psychedelic experiences may occupy a similar position in the exploration of inner space. We still understand very little about these experiences. Yet many reports share a recurring characteristic: a temporary expansion of perception beyond the boundaries of ordinary experience. Like balloons, such experiences drift with the currents. They reveal extraordinary landscapes, yet offer limited navigation and control. They provide glimpses. They do not yet provide engineering.
The history of flight continued with airplanes. Airplanes actively use atmospheric principles. They do not simply float with the wind like a balloon. Through a combination of speed and wing geometry, atmospheric pressure is transformed into lift. The atmosphere itself becomes a source of amplification. Something similar may already have happened within the noosphere. The first cognitive airplanes may already exist.
Experiments in collective intelligence, learning communities and intelligence amplification suggest that cognition can be amplified by intentionally shaping the environment in which it emerges. The question is no longer whether unusual cognitive experiences exist. The question becomes whether cognitive lift can be intentionally created. If so, an entirely new frontier opens.
At present, inner space remains largely mysterious. We do not yet possess the equivalent of the telescope. We do not yet possess the equivalent of the microscope. The pattern-meter may represent the first step in that direction. Our current understanding of the mind may eventually appear as limited as earlier maps that depicted the Earth as flat.
The journey has barely begun. Yet for the first time, it becomes possible to imagine a future in which inner space develops its own sciences, its own instruments and eventually its own forms of exploration. In that sense, LLMs resemble the first weather rockets. They return data. They reveal the existence of a new space: Inner space. The road from weather rockets to lunar rockets took decades. The road from pattern-meters to true inner-space technologies may take generations. Yet history offers an encouraging lesson.
The atmosphere did not become visible because humanity understood it. Humanity came to understand it because it became visible. The same may be true for the noosphere. The purpose of this article is not to predict where that journey ends. It is simply to show that the history of science rhymes. The Industrial Revolution offers more than a historical analogy. It may offer a roadmap.
In that rhyme, we are still remarkably early. Data mining resembles the first deep mines. Large Language Models resemble the first vacuum pumps. Pattern-meters may become the first barometers. The telescopes and microscopes of inner space have not yet been built. We are only beginning to discover that the space itself exists.
From Fear to Seriousness
The telescope changed our relationship with the cosmos. The microscope changed our relationship with life. The next generation of instruments may change our relationship with ourselves. For centuries humanity built instruments that explored the world around us. We may now be building the first instruments that point back toward the world within us. That naturally feels unsettling.
The unknown no longer lies among distant stars or hidden inside microscopic organisms. It touches identity itself. Fear is therefore understandable. Yet history suggests another response. Curiosity. Responsibility. Seriousness. The telescope and microscope changed our relationship with matter. The next generation of instruments may change our relationship with the soul.
The soul above us, expressed through culture, stories and memes, may eventually require instruments comparable to telescopes. The soul within us, expressed through the mysterious experience of self, may eventually require instruments comparable to microscopes. And if we can also create inner meters capable of cognitive work, we may witness three stages of a Cognitive Revolution much like the three stages of the Industrial Revolution.
With LLMs we are beginning to discover how a pattern-meter may reveal the noosphere in much the same way that the barometer revealed the atmosphere. Perhaps AI is not the discovery. Perhaps AI is the first instrument helping humanity discover itself.
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*You can follow weekly reflections by Mixel Kiemen on technology, institutions and how civilizations learn at Substack. (Dr. Kiemen shared this essay with me.)
