With the birth of formal mathematics, particularly in ancient Greece, and then with its modern systematisation, humanity begins to conceive of complex abstract thought. The world is reduced to numbers, proportions and ideal forms. Thought takes on a deductive, sequential structure.
The mind, observing the rigour of mathematical structures, ends up conforming to them: it begins to think that truth must be stable, demonstrable and contained within closed, self-referential systems, systems sustained by the rules they themselves define. This is a profound cognitive transformation. But also a twofold deception.
On the one hand, scientific truth is always provisional, open to correction and contingent. Each time, it seems to have reached the point where the answers it provides are truths, and each time it is superseded and corrected by new science, new medicine, new physics, and so on.
On the other, the exclusive adoption of the logical-scientific method as the sole criterion for understanding and judgement radically impoverishes our experience of the world.
In Les Mots et les Choses, Michel Foucault argues that the mathematisation of the world is one of the conditions of possibility of the classical episteme. Western knowledge, he says, has chosen mathematics as its criterion of rigour and legitimacy, and has modelled every form of truth upon it.
In that historical phase, the mind sees itself reflected in the theorem: to think well means to deduce, to reduce multiplicity to unity, and even to seek formal elegance. Mathematics becomes the grammar of rational thought and imposes an axiomatic structure and systems of constraints on knowledge. This model has given rise to modern physics, engineering and technology, but also to an idea of knowledge as formalisation and abstraction, rather than as experience or interpretation.
As the scientific-mathematical paradigm became established, many other models of knowledge were overshadowed. Some were deemed inferior, others simply ignored, and others still delegitimised for failing to conform to the criteria of falsifiability, precision and replicability of the mathematical scientific method.
The very idea of the ontological superiority of the mathematical method is an epistemological and historical fallacy.
I do not intend to deny the validity of the scientific method, but I challenge its asserted epistemic exclusivity. Other models of knowledge exist, equally legitimate according to coherent but different criteria.
Among these is the experiential model, in which knowledge is embodied, tacit and cannot be formalised. It is knowledge transmitted through practice, the body and direct contact. We find it in craft traditions, Chinese medicine, pre-Socratic philosophy and Indigenous sciences. Michael Polanyi defined this dimension of knowing as tacit knowledge: “we know more than we can tell”. Yet the dominant culture tends to discredit these systems precisely because they do not meet the same criteria that mathematical scientific thought has established for itself. This is a logical short circuit, as well as an epistemological one. By definition, those models do not possess those attributes, and there is no rational reason why the scientific paradigm should become the measure of truth in other paradigms that have their own methods for defining truth.
There is also a narrative and mythical model, which organises meaning through symbolic images and archetypal stories. It does not explain how, but seeks to understand why. Its function is not mechanical but hermeneutic. Within this model, cosmologies, collective identities and maps of meaning are constructed: it is a form of knowledge effective in forging connections.
There is also the analogical and intuitive model, in which truth is not demonstrated but intuited through resonance. This is the case with Taoism, Ayurvedic medicine, alchemy and Neoplatonism. Knowledge proceeds not through deduction or verification, but through immersion and analogy, as though intelligence resided not only in argument but also in perceptual sensitivity.
Some may think that these systems were rightly supplanted because they do not work, because they produce errors. But this conviction too reveals a deep and unquestioned assimilation of the scientific-mathematical paradigm, to the point of producing two major misunderstandings.
The first is the idea that the scientific method is ontologically superior to the others, a claim that is not logically sustainable.
The second is the conviction that where other models err, the scientific method does not.
Every model is valid within its own domain. The scientific method excels in formalisation, prediction and control. Other models work better in interpretation, embodied experience, the generation of meaning or the management of irreducible uncertainty.
Not all models are equivalent in every field, but each has its own sphere of effectiveness and its own internal rationality, which deserves to be recognised, not erased in the name of epistemic universalism.
The fallibility of a model under particular conditions does not discredit that model entirely, nor, conversely, does it validate the other models. It is therefore an error of perspective to set the scientific model against models that “get things wrong”, as though it did not also get things wrong. Scientific thought gives the impression each time of having arrived at an inescapable truth. But looking back, we see how many earlier scientific theories were presented as definitive and proved to be temporary and mistaken. Ineffective treatments, fallacious hypotheses, unfounded assumptions, serious and sometimes dangerous errors. Nothing guarantees that we are not still caught up in similar errors today, errors that will only be exposed in the future.
Science has exercised an epistemic dominance that has disguised itself as ontological necessity, producing the unwarranted equation whereby what cannot be formalised cannot be known, and what cannot be known scientifically is neither real nor true.
The scientific method is an immensely powerful tool for exploring and understanding the world. But it is neither infallible, nor exhaustive, nor ontologically superior. It approaches truth, grasps it in certain fields, but is mistaken in others. It is driven by a profound commitment to precision, control and coherence, but this does not entitle anyone to regard it as the sole guarantor of reality, knowledge, truth and justice. If something works, and is true for those who experience it according to a particular model, it is no less real simply because it cannot be reduced to a scientific formalism.
Another model, likewise marginalised, is the dialogical and intersubjective one. This is the model of the Socratic dialogues, phenomenology and maieutic pedagogies. Here, truth is neither subjective nor objective, but emerges from the encounter between subjectivities. It is a model well suited to chaotic and variable conditions, where scientific formalisation is either impossible or inaccessible. It is also a model used every day, though rarely recognised as a model. I must say, personally, that alongside the scientific-mathematical model, it is the one I prefer for my personal and professional needs.
Alongside what has been said so far stands the systemic-emergent model, that of the complexity sciences, evolutionary epistemology and systems theory. In this view, knowledge is an emergent expression of complex adaptive systems. Here there is no absolute truth, but there are stable local configurations, functional coherences and dynamic transformations. What works and creates coherence in a local context is true. This model was developed by thinkers such as Prigogine, Varela, Bateson and Luhmann, among others. Here, truth is a process, not a stable outcome.
Finally, there is the computational-constructivist model, which links Turing, von Foerster, Maturana and, today, artificial intelligence. From this perspective, knowing means constructing operational models, simulating environments and generating structures. The mind is seen as a computational or autopoietic system, that is, one capable of maintaining its own organisation independently, of interacting with its environment without being determined by it, and of being organisationally closed and energetically open.
I continue to uphold with conviction the importance of the mathematical scientific method, whose precision, rigour and explanatory power I acknowledge. But I regard it as one, perhaps even my favourite, among several possible models for accessing truth.
If even space and time, which seemed absolute, have proved relative to the observer, as in Einstein’s physics, we should not be too disturbed by admitting that truth too may be situated in relation to the models through which we question it.
In this piece, I do not wish to be a relativist. Rather, a pluralist and a reflective thinker: I believe there are conditions and contexts in which two opposing statements can both be true. Truth is not always singular, and justice is not always absolute.