A Unified Data Science

Towards a Philosophy of Science in the Age of AI

I feel that — at a time when data technologies, and generative AI in particular, are about to dramatically change our lives and societies — the moment has come for a philosophical reflection on data and science. This text is my attempt at such a philosophy. Philosophy is concerned with completion, with the recollection and unification of parts that have been separated. While my attempt here is somewhat extensive for a blog article, it is still far from comprehensive or complete. Yet this incompletion aligns well with the philosophy I outline, for the fundamental limitedness of science — and of data science — is one of its core principles. Completeness and absolution do exist, but only as something beyond science. Science, by contrast, strives for perfection: ever more accurate and concise, yet ultimately always limited descriptions of relative realities.

The central claim of this article is that modern science is best understood as a form of data-based reasoning with inherent limitations. For clarity, I use the term data science in a broad and inclusive sense, simply to denote science that deals with data. Recognizing the limitations of this data-based approach allows us to move toward a more unified understanding of science and mind and helps restore meaning within the scientific practice.

My approach to this philosophy is to mark out the territory of data science by clearly stating its limiting borders (its limes) in the form of simple statements — so-called aphorisms. These aphorisms serve as starting points for delving deeper into the various characteristics of data science, as well as for exploring truths and realities beyond what science can grasp.

The first aphorism opens the discussion by reflecting on how modern science has evolved into its data-centered form. It offers a historical and conceptual foundation for understanding why scientific inquiry today is inseparable from data — and thus how science has become data science.

For the explorations beyond science, I build particularly on the thoughts of A. N. Whitehead, C. G. Jung, Sri Aurobindo, and Swami Vivekananda. Whitehead, especially in Science and the Modern World, traced the evolution of scientific thinking from antiquity to modernity within the European intellectual tradition. Jung inquired into the processes of the psyche through extensive studies of “non-scientific” or “pre-scientific” material — mythology, alchemy, Gnosticism, dreams, and ethnographic sources — interpreting them psychologically, from a predominantly European perspective but with significant inspiration from Eastern philosophy. Aurobindo and Vivekananda deepen the understanding of mind and metaphysics from within the vast Indian philosophical tradition; at the same time, both spent substantial parts of their lives in the West, making them also vital bridge-builders between Eastern and Western thought.

With these foundations in place, we can now turn to the first aphorism.

1. “Science is reason grounded in facts”

Starting with an etymological consideration of the word data, it seems that it’s fist usage can be traced back to the 17th century to refer to “a fact given or granted,” or more specifically, in the context of mathematical problems, as “a fact given as the basis for calculation.” The term data — plural of datum, from Latin datum “(thing) given,” neuter past participle of dare “to give” — is closely related to the shift from a theory-oriented approach towards knowledge in natural philosophy to an observation-oriented approach in empirical science.

As A. N. Whitehead argues in Science and the Modern World, reason was already a highly sophisticated intellectual practice in ancient Europe and the Middle Ages. However, it was primarily applied to abstract domains, such as pure mathematics and spirituality. For example, reasoning in the Middle Ages was applied to fantastical problems, such as, “how many angles can be placed on the tip of a needle,” or “whether Christ could have accomplished his work of redemption if he had been born into the world as a pea” (examples retrieved from C. G. Jung, Psychology of the Unconscious). What was new at the beginning of modernity was applying reason to measurable facts — that is, reasoning based on data.

The prime example for the power of the new empirical paradigm is the Copernican revolution, that is, the shift from a geocentric to a heliocentric planetary model. The Ptolemaic model, the dominant model of the Middle Ages, placed the earth at the center of the universe and all other planets and the sun were turning around it. However Galileo’s observation of the phases of Venus, made possible by his invention of the telescope, irrefutably proved the Copernican model where the sun is at the center of our solar system and the earth is circling around it akin to all the other planets.

“In 1610 Galileo Galilei observed with his telescope that Venus showed phases, despite remaining near the Sun in Earth’s sky [(right image)]. This proved that it orbits the Sun and not Earth, as predicted by Copernican and Tychonic models [(right image)], and disproved the Ptolemaic one [(first two images)].” Source: https://en.wikipedia.org/wiki/Geocentric_model

The overwhelming success of Galileo’s empirical proof ushered in a new era, where sophisticated reasoning alone didn’t make up a fundament for a theory, but the results of reason now needed to be verified through facts and data.

On the flip side, this aphorism tells us that there are also non-factual reasoning and non-reasonable facts, both of which are not (data) science. Non-factual reasoning was the hallmark of the Middle Ages, but we still know it today in the minds natural tendency to ruminate over problems and all possible scenarios for ever. Eckhart Tolle compares the mind to a dog that picks up a scent and follows it headlong into the forest. When it finally returns to a reflective state of consciousness, it has no idea where it is — let alone how it got there. Another recent analogy has emerged in the technology of generative AI, where large language models can continue to hallucinate reasonably sounding chains of thought and sentences ad infimum. Grounding these models in facts has become a hot and difficult topic for today’s tech engineers but also for our society in general.

Non-reasonable facts are another hot and difficult topic, showing up in a world-wide political climate where the ad-hoc fabrication of “personal facts” seem to be on the rise — additionally boosted by the emergence of generative AI — while the conscientious and disciplined approach of modern science is under attack from different sides. We always knew that words and speech can be created by the mind quite freely, so the mindset of science started to demand for underlying facts. Data has become a synonym for facts.

As we will see later (in Aphorism 6), generative AI does not only challenge the notion of facts but also of reason. Modern science, building on the strong foundation of reason grounded in facts, may appear to be in a crisis today. However, I think, this crisis only concerns a certain claim to sole authority, where science sees reason and facts as the only valid instrument of knowledge. A Unified Data Science aims for a more truthful view by clearly outlining the limits of modern science. By creating awareness for the weak spots of the scientific method it actually aims at strengthening its core.

2. “Empirical evidence reveals a retrospective evolution process”

Over time, the colloquial term fact has evolved into the scientific notion of empirical evidence — data derived from sense experience or experiment. Karl Popper identified empirical falsification as a key criterion of science, describing progress as an evolutionary process: hypotheses arise, survive until disproven, and are replaced by more refined theories. This recursive cycle of testing and adaptation mirrors the evolutionary dynamics that Darwin observed in nature itself.

The crucial word in this aphorism is retrospective. Evolution — whether biological, scientific, or psychological — can only be observed after it has occurred. Empirical knowledge is therefore grounded in what has already happened — the past, which it can describe and analyze with accurate precision. However, it struggles to illuminate the future and everything that has not yet become manifest in the physical world.

To broaden the perspective, we can read evolution not only as a process in nature but also within human consciousness. The development of life and mind can be understood as an interaction of three archetypal poles: Nature (the living tree of growth and instinct), Spirituality/Divine (the radiant sun of transcendence and truth), and Reason/Intellect (the sharp sword of discrimination and law). For millennia, life unfolded in the dark womb of Nature. Early paganism and shamanism gradually brought light from the spiritual realm into this darkness. In Europe, the later import of Christianity, already highly developed in Reason and Spirituality, accelerated this ascent but also resulted in a repression of the pole of Nature.

Archetypal poles of life and mind: Nature, Spirituality/Divine, and Reason/Intellect. The disciplines and systems of alchemy, Christianity, and science can mainly be located at the intersections of two of these three poles. Image by the author.

C. G. Jung has described this process of somewhat hasty and artificial adoption of Christian Reason and Spirituality impressively in his Commentary on “The Secret of the Golden Flower”:

“We must never forget our historical antecedents. Only a little more than a thousand years ago we stumbled out of the crudest beginnings of polytheism into a highly developed Oriental religion which lifted the imaginative minds of half-savages to a height that in no way corresponded to their spiritual development. In order to keep to this height in some fashion or other, it was inevitable that the instinctual sphere should be largely repressed. Thus religious practice and morality took on a decidedly brutal, almost malignant, character. The repressed elements naturally did not develop, but went on vegetating in the unconscious, in their original barbarism. We would like to scale the heights of a philosophical religion, but in fact are incapable of it. To grow up to it is the most we can hope for.” — C. G. Jung, CW 13.70

Christianity thus stood at the intersection of Spirituality and Reason: it proclaimed an absolute truth (God) and an ultimate goal (redemption), while explaining human misery through rational causation back to the original sin and the fall from paradise. (Interestingly, the Fall was marked by eating the fruit from the Tree of Knowledge and the connected capacity to discriminate good from evil, and thus the birth of Reason.) Yet in these lofty abstractions between the initial sin and final redemption, Christianity lacked a sense of process — the slow growth and transformation inherent in Nature. Medieval alchemy, as Jung discovered in one of his major investigations, secretly carried on this missing evolutionary impulse, and can be seen a hidden continuation of pagan efforts to grow Spirituality out of Nature itself.

From this soil, modern science emerged at the junction of Reason, cultivated by Christianity, and Nature, explored by alchemy. Consciously, it appeared as a rebellion against both, insisting that truth must rest on observable evidence. But in rejecting the “unscientific” aspects of religion and alchemy, science also expelled their spiritual dimension. Together with spirituality, it lost the sense of intrinsic purpose and ultimate meaning. A resulting disorientation, showing up in a constant strive for progress without real direction, remains a hallmark of modern Western society.

Hence the word retrospective: empirical evidence helps us to understand the evolution of life and mind up to the present, but it cannot reveal toward what end this evolution moves. There is a certain general validity to the models created through understanding the footprints of the past, that can be successfully projected into the future. Predictions made by physics about trajectories of gross objects and particles are among the most remarkable in their precision and comprehension in this regard. Predictions can be made based on scientific models and reasoning. But predictions will never be scientific themselves. Science can only exist where there is empirical evidence. The more subtle — the more mind-like — the objects under study become, the harder it becomes to project understanding gained from the past into the future. Quantum physics is only the beginning of subtle here. In this regard, data can also be interpreted as living on the boundary between the gross, physical and the subtle, mental world, which will be the topic of the next aphorism.

Psychology resides at an interesting border between science and theories that go beyond empirical evidence and resemble more the investigations of former alchemy. For example, the fascinating documentary series The Century of the Self impressively documents how modern marketing developed in the 20th century in the US out of psychological theories, in particular Sigmund Freud’s theories about repressed desires. As we know, the influence and “predictive power” of marketing is by no means less powerful than the predictions of science. Yet, marketing will never be a strict science, as scientific rigor would starkly limit its imaginative and suggestive power.

Concerning the fate of alchemy, Jung concludes his studies about The Philosophical Tree with the statement:

“Alchemy lost its vital substance when some of the alchemists abandoned the laboratorium for the oratorium, there to befuddle themselves with an ever more nebulous mysticism, while others converted the oratorium into a laboratorium and discovered chemistry. We feel sorry for the former and admire the latter, but no one asks about the fate of the psyche, which thereafter vanished from sight for several hundred years.” — C. G. Jung, CW 13.482

In losing the psyche as the bridge between Nature and Spirit, science gained clarity but forfeited wholeness. The modern crisis of meaning, reflected in a rise of psychological distress, may well stem from this imbalance: by trusting only empirical evidence, we are missing a complementary intuitive and symbolic knowledge.

3. “Information is an artificial interface between the mind and matter”

As we trace the history of science into the 20th century, a new aspect of data has increasingly attracted scientific interest, whereby data refers to information. In particular, Einstein’s discovery of the equivalence of matter and energy, famously expressed as E=mc², concluded and thereby somewhat resolved the fertile polarity between matter and energy in which Newtonian physics has grown and flourished. A new polarity was needed between information (or structure) and energy-matter (the physical substrate) to create a fresh conceptual tension and to foster new fields such as quantum mechanics, statistical mechanics, information theory, and systems theory. These new fields led in particular to the creation of information processors (computers) and information networks (the internet).

In these newer sciences, data serves as a bridge between abstract thought and the physical world. It is at the same time the most material form of mind and the most mental form of matter — a projection of ideas into physical media and a symbolic representation of the world comprehensible to the mind.

Conceptual map of the information interface: data connects the mind and the world through models that interpret measurements and controllers that act upon the data, the world, and the mind. Image by the author.

As this aphorism emphasizes, information is artificial in the sense that it is consciously constructed by the intellect to extract or encode structure from or into a substance or medium. These artificial extraction and encoding processes build the foundation of the vast industry of information technologies — systems capable of reproducing, transmitting, and transforming information on a planetary and even inter-planetary scale.

While we are occupied in complex scientific thoughts and theories, it often happens that we forget about our natural interface between mind and matter that is already up and running since hundreds of thousands of years: our body. (At this point a quick shout-out to our bodies: let’s take a deep breath — inhale — and exhale.)

It is interesting to note that most fundamental scientific concepts, such as information, intelligence, energy, force, matter, and life, with their well-defined, artificial meanings within scientific applications, owe their inspiration to more natural meanings found in our bodies and nature that transcend the clear, narrow definitions of science. The concepts and products of science and engineering are artificial because they are conscious constructs of the intellect and reason.

Natural information, intelligence, energy, and so on, on the other hand, emerge and flow autonomously, regardless of whether our mind tries to understand and control them. A good example is our breath: we can either consciously observe and control it, or we can just let it go its way. Of course, the autonomy of our bodies and nature doesn’t mean our efforts to understand and control them have no impact at all — on the contrary, they can have a significant impact, for the better or the worse.

4. “Sound, images, language, and mathematics are the grids of the mind”

The artificial interface between the mind and the world is made possible by mapping the inherent grids of the mind into data structures which can be manifested in material form through technology. This aphorism is about further specifying these grids and it divides them into the four categories of sound, image, language, and mathematics. These categories are oriented largely on the different types of data structures that are used today. Of these categories, sound and image are connected closely to the specific auditory and visual senses — hence they form the main interface towards the physical world. Mathematics is the most abstract, least connected to the physical world. Language is somewhere in between, connected to the organ of speech, but at the same time building the structure for abstract thought.

There are other senses apart from auditory and visual — like smell, taste and touch –, other organs of action apart from speech — Samkhya philosophy reports further hands, feet, excretory organs, and reproductive organs — and other processes in the mind apart from language and mathematics — like feelings and emotions. Unlike sound, images, language and mathematics, these other senses, organs and processes do not have their corresponding (digital) data structures (yet?). Hence, there does not exist any grid through which they can be projected artificially back and forth between the physical world and the mind. The grids of the mind, as understood by this aphorism, are graspable both by the mind and by physically manifestable data structures.

Of the four categories, the most abstract mathematics is of special importance to modern science. With the digitalization, all data today is represented at some point as numbers and mathematical structures. And the recent generative AI models seem to make a strong case that the other three grids of sound, images and language can all be modeled and reconstructed based on numbers and mathematics. One could even argue that hence, for science, mathematics is the only true grid of the mind. Concerning the special role of “Pure Mathematics,” A. N. Whitehead suggested to claim it at least “the most original creation of the human spirit:”

“Another claimant for this position is music. But we will put aside all rivals, and consider the ground on which such a claim can be made for mathematics. The originality of mathematics consists in the fact that in mathematical science connections between things are exhibited which, apart from the agency of human reason, are extremely unobvious. Thus the ideas, now in the minds of contemporary mathematicians, lie very remote from any notions which can be immediately derived by perception through the senses; unless indeed it be perception stimulated and guided by antecedent mathematical knowledge.” — A. N. Whitehead, Science and the Modern World

While sound, images and language are more closely connected to the natural organs of hearing, sight, and speech, mathematics is, in Whiteheads word, “a resolute attempt to go the whole way in the direction of complete analysis, so as to separate the elements of mere matter of fact from the purely abstract conditions which they exemplify.” The miracle of mathematics is that, despite being the most abstract grid of the mind, it proves to be the most accurate and true description of nature and physical reality:

“Nothing is more impressive than the fact that, as mathematics withdrew increasingly into the upper regions of ever greater extremes of abstract thought, it returned back to earth with a corresponding growth of importance for the analysis of concrete fact. The history of the seventeenth century science reads as though it were some vivid dream of Plato or Pythagoras.” — A. N. Whitehead, Science and the Modern World

Some traditions rather place language to be the most fundamental grid of the mind — first and foremost Christianity with its Logos in the Gospel of John. The Logos and words are also the tools of philosophy. Art uses sound and images, and to a less extent language, as its primary media. While a hierarchy of the grids of the mind seems to depend on where one is coming from, for science the most fundamental structure is definitely mathematics.

But there are also attempts to use mathematics beyond science, to describe the non-physical reality or even the absolute reality. Astrology, numerology and Tarot are just a few examples. Also C. G. Jung was fascinated by the transcendental aspect of numbers and mathematics. A recent work by Harry Shirley draws on Jung’s concept of the unus mundus — a unified reality of matter, mind, and spirit — to connect the fractal structure of the Buddhabrodt (a particular subset of the Mandelbrodt set) with a wide range of mythological imagery, from the Buddha, to Ganesha, to Pharaohs, to alchemical emblems, to the Assyrian tree of life, to psychedelic art, to the Chakra system, to ancient architecture. This work raises the question if all these mythological and visionary imagery are revealing a truth about the fractal nature of absolute reality?

“Buddhabrot rendered with 1.000.000 iterations, second gamma-version.” Source: Wikimedia.

Despite all the phenomenal applications of digital data and mathematics, my main point here is to highlight that one should not fall for the illusion to confuse them with reality itself but identify them as grids of the mind instead. With Jung, such confusion can be seen as a participation mystique — a term he inherited from Lévi-Bruhl — as an “indefinitely large remnant of non-differentiation between subject and object:”

“When there is no consciousness of the difference between subject and object, an unconscious identity prevails. The unconscious is then projected into the object, and the object is introjected into the subject, becoming part of his psychology. Then plants and animals behave like human beings, human beings are at the same time animals, and everything is alive with ghosts and gods. Civilized man naturally thinks he is miles above these things. Instead of that, he is often identified with his parents throughout his life, or with his affects and prejudices, and shamelessly accuses others of the things he will not see in himself. […] He no longer works magic with medicine bags, amulets, and animal sacrifices, but with tranquillizers, neuroses, rationalism, cult of the will, etc.” — C. G. Jung, CW 13.66

Science, by seeing itself “miles” above the old primitive world views, can still fall for its own participation mystique, where it projects its own grids into nature and confuses mathematical laws with “natural laws.” In a similar vein, Whitehead identified a misplaced concreteness in the scientific world view at the source of nothing less than the ruin of modern philosophy:

“The great characteristic of the mathematical mind is its capacity for dealing with abstractions; and for eliciting from them clear-cut demonstrative trains of reasoning, entirely satisfactory so long as it is those abstractions which you want to think about. The enormous success of the scientific abstractions, yielding on the one hand matter with its simple location in space and time, and on the other hand mind, perceiving, suffering, reasoning, but not interfering, has foisted onto philosophy the task of accepting them as the most concrete rendering of fact. Thereby, modern philosophy has been ruined. It has oscillated in a complex manner between three extremes. There are the dualists, who accept matter and mind as on equal basis, and the two varieties of monists, those who put mind inside matter, and those who put matter inside mind. But this juggling with abstractions can never overcome the inherent confusion introduced by the ascription of misplaced concreteness to the scientific scheme of the seventeenth century.” — A. N. Whitehead, Science and the Modern World

5. “Change, progress, and optimization are the qualities of the mind”

After having talked about the grids of the mind, this aphorism is now addressing its qualities. The mind possesses a characteristic tendency to constantly seek improvement: it compares, evaluates, refines, and strives toward ever “better” states. Modern science often treats these tendencies as intrinsic qualities of nature itself, rather than recognizing them as intrinsic qualities of the observing mind; resulting again in a Jungian participation mystique — an unconscious projection of the subject into the object — or a Whiteheadian misplaced concreteness — the abstract dynamics of the mind are mistaken for inherent properties of nature. By attributing change, progress and optimization as qualities of the mind, this aphorism aims at separating the scientific object — nature or reality — from the scientific subject — the mind; and thereby breaking the spell that makes progress appear as a law of the nature rather than a function of the mind.

Optimization illustrates this confusion well. It is one of the central pillars of the scientific method: as I have described already in more detail in a previous blog post, nearly all modern scientific models, from physics to engineering to machine learning, are formulated as optimization problems. Whitehead traces the roots of this tendency back to the eighteenth century, when Maupertuis proposed the principle of least action as a metaphysical attempt to describe nature in terms “worthy of the providence of God.” This was a pivotal moment when mental ideals of perfection, reason, and economy were projected onto nature, transforming them into supposed natural laws. The modern view that the universe “minimizes” or “maximizes” anything is however less a discovery of nature’s inner workings than a reflection of the mind’s own preference for improvement, clarity, and order.

The realization that progress and optimization are rather qualities of the mind — the scientific subject and investigator — and not nature or life — the scientific object of investigation — came to me through the study of the Indian philosopher and yogi Sri Aurobindo. In yoga, the mind becomes itself the “subject” of study (in other words, the object :-)), providing objective insights into its workings and helping to resolve the confusion arising from the mind-matter duality on which science operates. (One of the great questions of yoga is then: who is this subject, when the mind becomes the object?) In The Synthesis of Yoga, Aurobindo differentiates between three layers of existence: material life, mental life, and spiritual life. Material life is characterized not by progress but by repetition and persistence:

“The characteristic energy of bodily Life is not so much in progress as in persistence, not so much in individual self-enlargement as in self-repetition. There is, indeed, in physical Nature a progression from type to type, from the vegetable to the animal, from the animal to man; for even in inanimate Matter Mind is at work. But once a type is marked off physically, the chief immediate preoccupation of the terrestrial Mother seems to be to keep it in being by a constant reproduction. […] such constant reproduction is the only possible material immortality. Self-preservation, self-repetition, self-multiplication are necessarily, then, the predominant instincts of all material existence. Material life seems ever to move in a fixed cycle.” — Sri Aurobindo, The Synthesis of Yoga, p. 25–27

The mind, by contrast, is intrinsically driven toward improvement:

“The characteristic energy of pure Mind is change, and the more our mentality acquires elevation and organisation, the more this law of Mind assumes the aspect of a continual enlargement, improvement and better arrangement of its gains and so of a continual passage from a smaller and simpler to a larger and more complex perfection. […] Change, then, self-enlargement and self-improvement are its proper instincts. Mind too moves in cycles, but these are ever-enlarging spirals. Its faith is perfectibility, its watchword is progress.” — Sri Aurobindo, The Synthesis of Yoga, p. 25–27

Spirit, last but not least, inherently and effortlessly embodies the eternity, perfection, and completeness for which material life and the mind are only ever striving for:

“The characteristic law of Spirit is self-existent perfection and immutable infinity. It possesses always and in its own right the immortality which is the aim of Life and the perfection which is the goal of Mind. The attainment of the eternal and the realisation of that which is the same in all things and beyond all things, equally blissful in universe and outside it, untouched by the imperfections and limitations of the forms and activities in which it dwells, are the glory of the spiritual life.” — Sri Aurobindo, The Synthesis of Yoga, p. 25–27

This triadic structure of material life, the mind, and spirit again sheds a new light on the major transition in Western history at the onset of modernity. According to Aurobindo, the mind is a graded series of levels of consciousness, ranging from the physical and vital minds to the rational mind (reason and intellect), the higher mind, the illuminated mind, intuition, the overmind, and finally, the supramental consciousness. Thus, reason is only one layer of the mind  —  the most important one for science. For most of human existence, material life  —  with its cyclic rhythms, traditions, and necessities  —  set the tone of collective existence. Reason and intellect were present but mainly turned inward toward the contemplation of inherited symbolic or metaphysical frameworks. However, during the Scientific Revolution, the material, technological, and social conditions arose that allowed the mind to turn outward toward the external world with an unprecedented force and power of reason. Europe thereby entered what Aurobindo called the “Age of Reason,” in which the mind’s internal drive for progress could manifest externally through experimentation, industrialization, and technological development.

This transformation unleashed unprecedented creative power, but it also came with a profound tension. Material life seeks stability and repetition; mental life seeks novelty, improvement, and expansion. As the mind imposes its restless dynamism onto the physical and social world, the friction between these two modes of existence intensifies — appearing as cultural acceleration, ecological strain, psychological exhaustion, and a widespread feeling of living in a perpetual crisis. Aurobindo sees this conflict not as an accident but as a transitional phase. Life cannot progress, and mind cannot unify. Their reconciliation, he argues, requires a higher synthesis or unification accomplished by what he calls the “supermind” — a higher mode of consciousness that harmonizes the stability of Life and the dynamism of Mind with the inherent unity of Spirit.

Viewed in this light, data science appears as a most accurate manifestation of the mind’s qualities. It formalizes progress into algorithms, converts improvement into loss minimization, and turns learning into mathematical optimization. Every dataset becomes something to be cleaned, refined, or expanded; every model becomes a prototype to be tuned and iterated. The optimization paradigm becomes so pervasive that it almost fades into invisibility, making it easy to forget that it is not a property of nature but of the mind.

6. ”Causality is correlation structured by reason”

Following the previous two aphorisms, which further specified the grids and qualities of the mind, we will now turn to a closer consideration of reason. As I mentioned earlier, reason constitutes a layer of the mind that is most important for scientific practice. The fundamental operation of reason is inference, or the process of structuring correlations as causations and explaining the world as a sequence of causes and effects. Classical physics clearly expresses this inferential reasoning: motion arises from force, inertia resists change, and friction dissipates energy. Statistical physics models build on this concept by acknowledging uncertainty in the causal chain and describing the world through distributions of likelihood rather than exact causation.

In contrast, machine learning primarily operates on the principle of fitting model parameters to observations. This process identifies correlations that enable prediction, without necessarily revealing underlying causes. Consequently, there is a common criticism that such models detect patterns but fail to understand them. Some branches, such as explainable machine learning and causal inference, attempt to bridge the gap between pattern recognition and inferential understanding. However, these methods still depend on domain experts to determine causal direction. For instance, conditional probabilities learned through causal inference remain symmetrical; the distinction between cause and effect arises only when a domain expert structures the data points in the form of a directed graph.

The same logic applies to recent reasoning models based on generative transformer-based language models. Their mechanisms — tokenization, positional encoding, attention — are mathematical operations of correlation. Yet, in the paper On the Biology of a Large Language Model researchers from Anthropic demonstrated through an elaborate analysis that large language models, consisting of only positional encoding and many attention layers stacked on top of each other and trained on vast amounts of text data, start to exhibit emergent properties of causal reasoning. These properties include “two-hop reasoning […] to identify that the capital of the state containing Dallas is Austin,” and “outputs ahead of time when writing lines of poetry.” Once again, however, there is no distinct “causation module” in the model’s architecture. Reason itself arises from the sequential structure of the training data — language — and the “non-causal” mechanisms of positional encoding and attention. Attention consists of a correlation in an augmented mathematical space, followed by a softmax operation that focuses on only a small subset of all possible correlations.

Transformer model architecture, the foundation of large language and reasoning models, as outlined in the seminal Attention Is All You Need paper by Ashish Vaswan, et. al. Left part: full encoder-decoder transformer architecture, including embeddings, positional encoding, and multiple attention layers. Right part: Single scaled dot-product cell. The Dot Product and MatMul together basically correspond to correlations of the query (Q), key (K), and value (V) vectors and the Softmax focuses the attention on only a small subset of all correlations. Source images: author combining two images from Wikipedia.

Developments in machine learning and generative AI seem to support the view that causation is not an external law discovered in nature, but rather a projection of the mind’s internal structure imposed on the data. Upon closer examination, every causal chain dissolves into patterns of association. Only reason restores them back into narratives of cause and effect.

Beyond causation and reason, correlation can also be understood as resonance — an interconnected field of vibrations rather than a linear chain of cause and effect. C. G. Jung viewed this concept through the lens of synchronicity, which posits that meaningful coincidences defy causal logic yet hint at an unseen order binding the psyche and the world. Similarly, physicist Anirban Bandyopadhyay describes matter not as isolated particles but as interwoven electromagnetic resonance chains, where coherence emerges through synchronized vibration rather than mechanical causation. His experiments reveal that molecular, cellular, and neural structures exhibit self-similar frequency patterns across a wide range of scales, what he calls Triplets-of-Triplets. His vision of reality as a symphony of nested vibrations, reminiscent of the Buddhabrot fractal, suggests the idea that consciousness itself may appear as a living pattern of electromagnetic resonance — a visible rhythm of the mind, as recently described in a portrait of Bandyopadhyay’s work.

As Bandyopadhyay’s concepts of resonance chains chains transcend the idea of cause and effect, they also transcend the concept of linear time, in which all events occur in an absolute, sequential order. Instead, he adopts a fractal view of time, where time is a superimposition of cycles at various speeds — a “clock inside a clock inside a clock.” In such a world, events do not simply follow each other, but rather resonate with each other. What we usually experience as sequence may well be a vast, timeless field of coherence projected into the particular harmonic or vibration of reason.

Images by Anirban Bandyopadhyay’s research group. Left images: “Self-similar resonance bands for neuron, microtubule and tubulin; (a) Microscope image Au electrode grid, rat hippocampal neuron, scale bar = 10 µm […]; (b) Atomic force microscopy (AFM) of a single microtubule, scale bar = 120 nm […]; © AFM of a tubulin substrate, scale bar = 50 nm.” — source: Fractal, Scale Free Electromagnetic Resonance…; Right image: plot of combinatorial number of prime factorizations of natural numbers as possible explanation of fractal structures of measured frequency patterns — source: A Brain-like Computer Made of Time Crystal…; See also Bandyopadhyay’s TED talk on Patterns: From Proteins to AI.

This brings us back to our discussion of artificial versus natural, and mind versus matter. It seems to me that the world consists of a natural mind that exists in different frequencies. This corresponds to the subtle world. Conversely, there is a gross, artificial world consisting of objects and matter that are somehow constructed through intellect and reason. Quantum mechanics can be seen as a bridge between these two worlds. In this model, the vibrations and frequencies of the subtle, living mind collapse into gross, artificial matter. Matter becomes dead in this process, but at the same time accessible to the intellect and reason. Rather than the collapse of “particles,” it is the collapse of a worldview — from a vibrational view of resonance and responsiveness to a rational view of separation and causation. This suggests that death itself may be merely an intellectual concept. As long as we perceive the world as subtle, wet, and fluid vibrations, it is alive. When our view collapses into gross, dry, and rigid matter, things become dead.

From these thoughts it becomes clear that the abstract idea of an endurable object and death arise mutually. The two maxims of data, that it should consume as few disk space as possible — be as light as possible — and at the same time be as endurable and long-living as possible, suggest that data is striving towards this abstract idea of an eternal object. It becomes at once a means to transcend death, preserving form and information indefinitely, and the very materialization of death in its rigidity and absence of vibration. “Data is dead” seams to make a just antidote to Nietzsche’s “God is dead.”

Yet just as God has not truly died — it is only our responsiveness to the divine that got lost — so data is not truly dead. It carries latent vibrations that can be reawakened in the mind: when reading words of long-past thinkers like Jung or Vivekananda, listening to a beloved song, or gazing at an old photograph. In such moments, seemingly dead data comes alive again, resonating with consciousness and restoring connection across time. In order to receive such signals from seemingly dead data, we must open our hearts and minds to their vibrations by stepping out of a solely reason-based perspective on data points.

7. ”Science is conscious ignorance”

At this point, science and reason seem to show an ambivalent record. They bring enlightenment and knowledge but also a lack of meaning and ultimately, death. The sword of reason comes with two edges: it cuts through the darkness of illusion but also through the veins of life.

This final aphorism aims to reconcile the insoluble paradox by uniting the irreconcilable opposites and arriving at A Unified Data Science. The way to do this is to clearly recognize the paradoxical nature of science.

Swami Vivekananda, in The Ideal of a Universal Religion, talks of three instruments of knowledge: instinct, reason, and inspiration. He calls instinct an “inadequate instrument” to which the “sphere of action is very limited.” But also reason finds before it a “mighty barrier […], beyond which [it] cannot go:”

“Reason can go only a little way and then it stops, it cannot go any further; and if you try to push it, the result is helpless confusion, reason itself becomes unreasonable. Logic becomes argument in a circle. Take, for instance, the very basis of our perception, matter and force. What is matter? That which is acted upon by force. And force? That which acts upon matter. You see the complication, what the logicians call see-saw, one idea depending on the other, and this again depending on that.” — Swami Vivekananda, Jnana Yoga, p. 451

The key lies in recognizing these instruments as developments of each other, and not as contradictions:

“It is reason that develops into inspiration, and therefore inspiration does not contradict reason, but fulfils it. Things which reason cannot get at are brought to light by inspiration; and they do not contradict reason. The old man does not contradict the child, but fulfils the child. Therefore you must always bear in mind that the great danger lies in mistaking the lower form of instrument to be the higher. Many times instinct is presented before the world as inspiration, and then come all the spurious claims for the gift of prophecy. […] The first test of true teaching must be, that the teaching should not contradict reason.“ — Swami Vivekananda, Jnana Yoga, p. 454

At this point, I am still wondering if this clear hierarchy from instinct to reason to inspiration is the final answer. Or is it again a sequential, an hence reason-dominated, view of the evolutionary process? As we discussed in Aphorism 2 and in the image showing the three poles of Nature, Spirituality, and Reason, evolution could be understood as a circular process. Natural instinct opens up to spiritual inspiration and intuition through paganism and alchemy, which then develop into reason. Similarly, in practice, inspiration and intuition are often accessed through reconnecting our mind with our body rather than through rising into ever higher states of mind. However, Vivekananda’s main contribution is probably that he integrated reason and science into spirituality, paving the way for a new openness to spirituality and religion in the West at the end of the 19th century, when God had “died” under the science-dominated worldview of the time.

Apart from that, Vivekananda also addressed the question of whether science can go beyond reason toward inspiration? Inspiration is certainly an important driving force behind scientific progress. However, science’s core task lies in overcoming this “most contradictory irrational nonsense.” To maintain its integrity, science should focus on this core task. Rather than aspiring to be the sole source of knowledge, science should acknowledge its boundaries, which are defined by the inherent limitations of reason and measurement technology. Science should push these boundaries incessantly while constantly acknowledging and communicating that it will never be able to understand or know all there is.

The way is to become aware of the ignorance inherent in the scientific method. The ignorance of science is manifold. Firstly, the strength of science is its immense focus on cutting out one aspect of reality and trying to understand it rationally, step-by-step, and in all detail. This kind of understanding enables reproducibility and technological innovation. But with the conscious decision to focus on one aspect of reality, one is inherently ignoring many other aspects. The same argument applies to the measurement process and data collection: the conscious decision to collect one particular data point brings focus to this one point but ignorance to all other measurements that could have been taken. Similarly, the attribution of scientific discoveries to particular persons (usually men), ignores the “giant” of other contributors on whose “shoulders they were standing.”

In this sense, ignorance can be seen as the other side of focus: focus brings both clarity and ignorance. Therefore, the integrity of science depends not only on what it observes, but on its awareness of what it ignores.

I first encountered this idea of inherent ignorance in science in Alan Watts book Psychotherapy East and West, where he writes:

“In one way the repeatable experiments of science are based on ignore-ance, for they are performed in artificially closed fields. But these experiments add to our knowledge just because the scientist knows that he is ignoring. By rigorous isolation of the field he gets more and more detailed knowledge of the way in which fields are, in practice, related to each other. He does not ignore ignore-ance.” — Alan Watts, Psychotherapy East and West

Another name of ignorance is the misplaced concreteness of Whitehead above. Yet another name is the ego or ego-consciousness. In his book, Watts makes the connection between his ignorance of ignore-ance, and ignorance as the fundamental source of suffering taught by Eastern philosophies. The ignorance of Eastern teachings is about taking the ego, the sense of a separate and autonomous self, for absolute reality. Freedom of suffering is not about denouncing the ego as a mere illusion, but becoming fully aware of its limitations and ignorance. In the words of Aurobindo:

“There is a sense in which these pretensions of the human mind and ego repose on a truth, but this truth only emerges when the mind has learned its ignorance and the ego has submitted to the All and lost in it its separate self-assertion. To recognise that we, or rather the results and appearances we call ourselves, are only a partial movement of this infinite Movement and that it is that infinite which we have to know, to be consciously and to fulfil faithfully, is the commencement of true living.” — Sri Aurobindo, The Life Divine, p. 76

Yet another name of ignorance is the veil. In this medium article, the author describes the veil as “a structural membrane in consciousness — a layer of latency woven into hum[an] perception so the nervous system could process reality in sequence […] a delay between cause and effect, thought and manifestation, perception and proof.” In his speech The Absolute and Manifestation delivered in London in 1896, Vivekananda said that “the Absolute is manifesting Itself as many, through the veil of time, space, and causation.” We can cut through the veil of ignorance by becoming aware of the limitations that reason puts on us and by opening up for the Absolute, the Oneness which lies beyond. Later in his speech, Vivekananda envisioned a future where science, religion, and philosophy meet in a common strive towards Truth and Oneness.

“We want today that bright sun of intellectuality joined with the heart of Buddha, the wonderful infinite heart of love and mercy. This union will give us the highest philosophy. Science and religion will meet and shake hands. Poetry and philosophy will become friends. This will be the religion of the future, and if we can work it out, we may be sure that it will be for all times and peoples. This is the one way that will prove acceptable to modern science, for it has almost come to it. […] The Hindu nation proceeded through the study of the mind, through metaphysics and logic. The European nations start from external nature, and now they too are coming to the same results. We find that searching through the mind we at last come to that Oneness, that Universal One, the Internal Soul of everything, the Essence and Reality of every-thing, the Ever-Free, the Ever-blissful, the Ever-Existing. Through material science we come to the same Oneness.” — Swami Vivekananda, Jnana Yoga, The Absolute and Manifestation

The way into a bright future of humanity is not about either-or — not either science or spirituality — but about and — both — not one linear path, but non-linearity — like a quantum particle that takes all possible paths at once — not duality, but non-duality — union. A Unified Data Science therefore calls for awareness of the limits of science — awareness of ignorance — as the central principle of its method. To be scientific is to look with focus; to be wise is to know the one-sidedness of that focus. Like Socrates said, “I know that I know nothing.” By recognizing the limits of every model and the silent assumptions of every observer, science not only strengthens its intellectual honesty but also nurtures psychological and spiritual balance, and thereby nurtures the soil for growing a unified and inspirational knowledge that transcends reason, clears the veil of ignorance, and dissolves the false identifications of the ego.

Conscious ignorance transforms limitation into wisdom. It is the humility that keeps reason alive, the calmness that guards the flame of understanding, and the space in which knowledge can continue to grow.