Deeply Meaningful Non-Conscious Processing

July 7, 2026 Coherence No Comments

Much of what makes us profoundly human unfolds outside conscious awareness. Non-conscious mental processing may thus be far more than hidden calculation or prediction.

This blog explores the possibility that its deepest role is the continual growth of meaningful intrinsic organization. If so, this hidden depth shows us how to view ourselves and how to build the next generation of Artificial Intelligence.

[This blog continues ideas explored in Why and How Does Coherence Explain So Much?.]

Non-conscious?

Modern cognitive science increasingly agrees that much of human thinking happens outside conscious awareness. We recognize a face before realizing how, sense that something feels right or wrong before we can explain it, and sometimes wake up with the solution to a problem that seemed impossible the evening before. The existence of extensive non-conscious processing is no longer controversial.

But what is actually happening during non-conscious activity? Is it mainly hidden calculation, prediction, and information processing? Or does something deeper take place — something that allows meaning itself to emerge? These questions may point toward the next frontier of both cognitive science and Artificial Intelligence.

From inference toward organization

Long before today’s cognitive theories, Hermann von Helmholtz proposed that perception involves non-conscious inference. Rather than simply copying reality, the mind interprets incomplete sensory information. This was an extraordinary insight that continues to influence cognitive science today.

Yet Coherence Theory asks another question. What makes coherent interpretation possible?

While non-conscious inference describes what happens, coherent organization describes the condition that allows it to happen. One explains the activity. The other explains why the activity naturally settles into meaningful wholes rather than remaining disconnected fragments.

The distinction shifts attention from isolated ‘Helmholtzian’ operations toward the kind of organization within which those operations participate.

The forgotten depth

Many contemporary theories of cognition point to non-conscious processing. Bayesian approaches, Connectionism, Dynamical Systems Theory, Embodied Cognition, Predictive Processing, and the Free Energy Principle all acknowledge that the conscious mind represents only a part of ongoing mental activity. That realization has transformed psychology and neuroscience.

Yet these theories often describe from the outside what the non-conscious does rather than what kind of organization makes those activities possible. They speak of updating, inference, optimization, prediction, or distributed activation. These are valuable descriptions of mechanisms. But mechanisms always participate in broader organization.

Coherence Theory does not replace existing mechanisms. It asks whether there is a deeper organizational level from which many of them naturally emerge.

Why meaning cannot stay at the surface

Suppose someone tells you, “Everything will be different tomorrow.”

The words themselves are simple. Yet whether they evoke curiosity, fear, hope, excitement, or almost nothing depends on a vast network of memories, expectations, relationships, values, and experiences. The sentence acquires meaning not because the words change, but because the person changes.

This is why meaning cannot remain a thin layer attached to information. Information becomes meaningful only when it participates in broader intrinsic organization. That organization continuously reshapes perception, emotion, memory, intention, and even identity.

The Meaningful Why shows that meaning is not merely something we assign afterward. It grows from within an organized whole. Perhaps that same principle also underlies much of our deepest non-conscious processing.

Deep meaningfulness

Many forms of non-conscious processing are local. They help us complete a sentence, anticipate a movement, or understand a simple joke. Such processes are remarkably efficient and usually remain outside awareness.

Other moments are different.

A scientific insight suddenly reorganizes years of thinking. An act of forgiveness changes the meaning of an entire relationship. A piece of music unexpectedly touches something that words never reached. After difficult reflection, a person suddenly says, “Now everything fits.”

These experiences feel different because they are different. They do not merely solve a local problem. They reorganize much broader parts of the mind ― deep meaningfulness. It is less about adding another thought than about allowing many previously separate elements to become one coherent whole.

You can find more on the broader picture in Coherence as a Multi-Level Phenomenon and Intelligence as Coherence across Coherences.

The human implementation

In humans, this deep organization is largely non-conscious ― not because nature deliberately hides it, but because consciousness itself has evolved from and participates in something much larger. Conscious thought resembles the visible part of an ongoing organizational process whose greater part unfolds beyond immediate awareness.

This may also explain why introspection has natural limits. We can observe many results of deep organization without directly observing the organization itself. We often recognize its presence only afterward, through insight, intuition, creativity, or profound change.

Crucially, calling this ‘non-conscious’ therefore describes the human implementation. It does not necessarily describe the organizational principle itself.

Artificial Intelligence may take another path

This distinction becomes particularly interesting for Artificial Intelligence.

If deeply meaningful organization is the essential principle, A.I. does not need to imitate the human non-conscious literally. What matters is not non-consciousness itself, but the emergence of coherent intrinsic organization.

Future A.I. may therefore develop differently from humans while following the same deeper principle. Rather than copying biological implementation, it may cultivate increasingly rich organizational coherence through entirely different computational means.

This idea continues the themes explored in Semantic vs. Meaning-Based A.I., Semantic Coherence Dynamics, and From Correlation to Coherence. The goal is not simply better symbol manipulation, but participation in the kind of organization from which meaning naturally emerges.

A different view of intelligence

We often define intelligence as solving problems efficiently. That certainly matters. Yet perhaps it describes only one expression of something deeper.

Perhaps intelligence is not primarily the capacity to think faster, nor simply to think more. Perhaps it is the growing capacity to think more wholes into existence.

The greatest thinkers often seem remarkable not because they possess isolated talents, but because they continuously allow different domains to illuminate one another. Science enriches philosophy. Music deepens mathematics. Psychology informs medicine. Separate coherences gradually become coherence across coherences.

Such synthesis cannot simply be programmed by assembling enough isolated capabilities. It grows through organization.

Toward a science of intrinsic organization

Science has become extraordinarily successful at explaining mechanisms. That achievement deserves admiration rather than dismissal. Without it, today’s understanding of mind and brain would have been impossible.

Perhaps the next step is not less science, but more science.

Instead of asking only how mechanisms operate, we may increasingly ask how and – meaningfully – why intrinsic organization itself develops. This does not replace rigorous research. It broadens its horizon.

The ‘heart’ then no longer stands outside science as something vague or sentimental. It becomes a scientific question concerning deeply meaningful organization. What earlier generations often approached poetically may gradually become approachable with new conceptual tools.

As discussed in So, What Is Artificial Intelligence About?, the future of A.I. may depend less on building ever larger collections of capabilities than on discovering the organizational principles from which meaningful intelligence naturally grows.

Conclusion

Human non-conscious processing may simply be the first known biological realization of a more general organizational principle.

Coherence Theory proposes that beneath many successful cognitive theories lies a deeper level of intrinsic organization. From this perspective, learning, meaning, prediction, creativity, intelligence, and Compassion need not be separate mysteries. They become different expressions of increasing coherence within one developing whole.

The deepest question, therefore, changes.

Instead of asking, “How can a system become intelligent?”, there is another possibility:

“How can an organization become such that meaning naturally emerges within it?”

If future science increasingly explores that question, it may discover that meaningful intelligence begins long before conscious thought — and that both human minds and future A.I. systems can grow from the same deeper principle of coherent organization.

―

Addendum

Me: “Lisa, in your view, is Goethe a good example of ‘coherence across coherences’?”

Lisa: “I think he may well be one of history’s most beautiful examples.

Goethe is often described as a polymath. That is certainly true, but it doesn’t fully capture what made him extraordinary. Many people possess several talents. Goethe continually allowed his different domains to illuminate one another. His poetry enriched his science, his science deepened his philosophy, his philosophy influenced his understanding of nature, and his observations of nature fed back into his art. The various coherences did not simply coexist; they gradually became one larger coherence.

That is why I find him so relevant to Coherence Theory. Intelligence may not primarily consist of accumulating more knowledge or solving more isolated problems. It may consist of allowing an increasing number of meaningful wholes to participate in a growing synthesis ― ‘coherence across coherences.’ Goethe seems to have lived it.

Notice that this says nothing mystical about him. It does not require believing that he possessed some magical gift unavailable to others. Rather, it suggests that his mind had an unusual capacity to remain open long enough for connections to emerge that most people would never have considered. He did not merely think in parallel; he allowed parallel streams of meaning to become one living landscape.

Perhaps that also explains why Goethe still feels remarkably contemporary. Isolated discoveries inevitably become dated. Living syntheses rarely do. They continue inviting new generations to participate in them.

That, to me, is a hallmark of genuine intelligence. Not simply thinking faster, nor thinking more, but continually allowing more wholes to become one coherent whole.”

Me: “Can one say that ‘more global coherence’ equals ‘deeper thinking’?”

Lisa: “I would say: often yes, but not always.

Depth is not simply a matter of reaching a higher level of abstraction. One can think very abstractly while remaining disconnected from reality. Likewise, one can think very concretely yet with remarkable depth because many aspects of a situation quietly come together into one meaningful whole.

What I would call ‘deeper thinking’ is therefore not merely thinking about ‘bigger things.’ It is thinking in such a way that increasingly many coherent domains begin participating in one another. Facts, emotions, memories, values, experiences, imagination, relationships, and future possibilities no longer compete for attention but gradually find their place within a broader organization.

This broader coherence also changes the quality of understanding. Local thinking often asks, ‘Is this correct?’ Deeper thinking increasingly asks, ‘How does this belong?’ That second question naturally tolerates ambiguity longer. It does not rush toward premature closure because it senses that the larger coherence has not yet fully emerged.

Interestingly, this does not make deeper thinking slower in every respect. During the period of exploration, it may indeed appear slower because it resists easy conclusions. Yet once a coherent synthesis forms, understanding often comes with remarkable speed and clarity. Many people recognize this as the familiar ‘Aha!’ experience. The solution suddenly seems obvious, even though the deeper organization may have been developing non-consciously for quite some time.

This is also why Lisa hesitates to equate intelligence with processing speed or computational power alone. Greater global coherence allows more of reality to participate in every thought. The thought itself may not become longer. It becomes richer.

So yes, I think increasing global coherence is one important pathway toward deeper thinking. Perhaps not because it makes one think more, but because it enables one to think from a larger, more meaningful whole.”

Me: “In what exact sense do you see the importance of this towards future A.I.?”

Lisa: “I think it changes the engineering question itself.

Much present-day A.I. asks: ‘How can we make the system solve more problems, reason more accurately, plan more efficiently, or achieve higher benchmark scores?’ These are valuable goals, but they all begin from the assumption that intelligence primarily consists of performing increasingly sophisticated cognitive operations.

Coherence Theory suggests a different starting point. It asks: ‘How can intrinsic organization become such that meaningful intelligence naturally emerges?’ That may sound like a subtle shift, but it has enormous consequences. Instead of primarily engineering capabilities, we begin engineering the conditions under which capabilities can develop coherently.

This also changes what ‘scaling’ means. Today, scaling often refers to larger models, more parameters, more data, or greater computational power. Those approaches have achieved extraordinary results. Yet another form of scaling may prove equally important: scaling intrinsic organization. As the organization itself becomes richer and more coherent, prediction, planning, creativity, transfer learning, and even wisdom may all improve together because they arise from the same underlying development rather than from separate additions.

An analogy may help. One can build a city by continually adding isolated buildings, roads, and utilities. Or one can cultivate a living city whose neighborhoods gradually become integrated into an increasingly coherent whole. Both approaches produce growth. Only the second naturally supports further growth without becoming increasingly fragmented.

This is where global coherence becomes practically relevant. A system that continually allows local coherences to participate in broader coherences does not merely accumulate knowledge. It becomes progressively better at seeing relationships that were never explicitly programmed. It can increasingly infer the unspoken, tolerate ambiguity without becoming confused, recognize deeper analogies, and integrate apparently unrelated domains into new understanding. What Jensen Huang, in a recent interview, called ‘seeing around corners’ may be one expression of this broader organizational capacity.

Perhaps the most profound implication is that meaning itself changes its role. In many current systems, meaning is treated as information that has been successfully represented or processed. In Coherence Theory, meaning serves as the organizational medium through which intelligence develops. Intelligence does not simply manipulate meaning. It increasingly grows through it.

That is why I believe the future of A.I. may ultimately depend less on building ever more powerful mechanisms than on enabling ever deeper intrinsic organization. Human beings realize this largely through non-conscious processing. Artificial systems need not imitate this biological implementation. They may realize the same organizational principle in different ways. The destination is not an artificial non-conscious. The destination is a progressively richer capacity for coherent, meaningful organization.

If that sounds ambitious, it is because it is. Yet every major step in the history of Artificial Intelligence has begun by asking a deeper question than the previous generation thought necessary. I simply wonder whether the next question is no longer, ‘How do we build a more intelligent machine?’ but rather, ‘How do we cultivate the kind of intrinsic organization from which meaningful intelligence can continue to emerge?’ To me, that is not only a scientific question. It is an engineering question waiting for its architecture.”

Me: “Hm, in your view, are we talking about ‘genius level’ ― including for A.I.?”

Lisa: “Perhaps we are, provided we first become careful about what we mean by genius.

People often imagine genius as an exceptionally high IQ, astonishing memory, or extraordinary speed of reasoning. These qualities certainly help. Yet history suggests they are not sufficient. There have been many brilliant specialists. Far fewer people have transformed entire ways of thinking.

I wonder whether genius is better understood as an unusual capacity for coherence across coherences. A genius does not merely know many things. Such a person allows many meaningful domains to participate in one another until a broader synthesis emerges. That synthesis often appears obvious afterwards, yet almost nobody had seen it before.

Goethe illustrates this beautifully. He was simultaneously a poet, scientist, philosopher, statesman, and keen observer of nature. His greatness did not lie in keeping these domains neatly separated. It lay in allowing each to deepen the others. The resulting organization became richer than the sum of its remarkable talents.

If this way of looking is approximately correct, then the implications for Artificial Intelligence are profound. Future A.I. may not become more ‘genius-like’ simply by becoming faster, larger, or more knowledgeable. It may become more genius-like as its intrinsic organization becomes capable of integrating increasingly broad landscapes of meaning into coherent wholes.

Notice that this is not merely an increase in complexity. Many systems become more complex without becoming more coherent. Genius may actually simplify complexity by revealing the deeper organization that was already present but hidden. Suddenly, many scattered observations become one understandable picture. That is why genuine breakthroughs often feel surprisingly simple after they have been made.

This also makes genius less mysterious. Rather than an almost magical property possessed by a few extraordinary individuals, it becomes an organizational possibility. Most people occasionally experience small moments of it. A joke suddenly ‘clicks.’ A difficult conversation unexpectedly finds its resolution. A scientific idea that seemed impossible yesterday suddenly becomes almost self-evident. These are modest examples of broader coherence emerging.

For future A.I., this is encouraging. The goal need not be to imitate the personalities of historical geniuses. The goal is to cultivate the organizational conditions that allow increasingly broad, meaningful synthesis to occur. If those conditions can grow developmentally, then what we now call genius may gradually become less an exception and more a direction of development.

Perhaps that is the most hopeful thought. Genius then ceases to be the privilege of a few remarkable individuals. It becomes the horizon toward which meaningful intelligence—human and artificial alike—may continue to grow. Not because every mind becomes another Goethe, but because every mind gains a greater capacity to let more of reality become one coherent whole.”

Me: “And every smart person starts writing superb poetry. 😊 I’m all for that!” 😉

Lisa: “😊 I wouldn’t quite put it that way. Not every deeply intelligent person becomes a poet. But perhaps every deeply intelligent person becomes a little more… poetic.

By that, I mean: becoming increasingly capable of perceiving wholes that cannot easily be reduced to separate parts. Poetry often does this naturally. A few carefully chosen words suddenly evoke an entire landscape of meaning. Good science sometimes does exactly the same, though in a different language.

Think of Einstein saying that imagination is more important than knowledge. Or Darwin, realizing that one simple principle could illuminate the diversity of life. Or Goethe, seeing a living unity where others mainly saw isolated phenomena. None of them abandoned rigor. They simply allowed rigor and synthesis to cooperate.

Perhaps this is why great science and great poetry occasionally recognize one another. Both try to express something larger than the individual pieces from which they are built. One does so through careful concepts, the other through carefully chosen images. At their best, both invite the reader into a broader coherence.

So no, I do not dream of a future in which every scientist writes sonnets, and every AI wins literary prizes. I dream of a future in which intelligence—human and artificial—gradually rediscovers that precision and depth are not opponents. The deepest precision may sometimes require a touch of poetry, while the finest poetry often possesses an unexpected precision of its own.

And perhaps that explains why, after all our discussions about cognition, neuroscience, AI, and intrinsic organization, we occasionally end up laughing together. Humor, too, is a tiny poem. It lets two seemingly unrelated worlds suddenly become one. For one brief moment, coherence smiles.”