The Hidden Ontology of Observation: How Human Perception Determines the Limits of Scientific Inquiry
1. Introduction: A seemingly trivial insight with a deeper problem
The statement initially appears banal: humans perceive the world only partially. We do not see infrared light, we do not hear ultrasonic frequencies, and we do not feel magnetic fields. What we experience as “reality” is therefore always already a selected version of what is physically present.
This observation is hardly surprising in everyday life. It belongs to the general educational background of modern societies. And yet, its philosophical implications are rarely followed through consistently in scientific thinking.
Because once this observation is taken seriously, the very foundation of scientific knowledge begins to shift.
Scientific methods are usually understood as tools for capturing an already given reality as precisely as possible. Their limitations are typically discussed as methodological issues: imprecise measurements, small sample sizes, modelling assumptions, or systematic biases.
However, this perspective silently assumes that the starting point—the humanly perceivable world—is already sufficiently representative of “reality.”
The real question, however, is:
What if this very starting point is itself only a highly restricted slice of what reality encompasses?
2. The implicit foundation of scientific knowledge
Every empirical science rests on a silent basic assumption:
- There is an external reality.
- This reality is in principle observable.
- Observation can be recorded through research methods.
- This measurement produces knowledge about this reality.
This structure is deeply embedded in the natural and social sciences and forms the basis of what is often understood as scientific realism—in its classical form, for example, in epistemological positions associated with Karl Popper.
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| Picture: Deon Black on Unsplash |
Popper assumes that there is an objective reality independent of our theories, which scientific knowledge can asymptotically approach. Falsification serves as a methodological mechanism enabling approximation, but not complete capture.
Yet even within this framework, one crucial question remains open:
Does this approximation apply only within the humanly accessible experiential world—or to reality as such?
This is where the real shift in perspective begins.
3. The world as it appears—and the world as it might be
Human perception is not a neutral channel. It is a biologically specialized filter.
Our sensory systems are evolutionarily tuned to process only certain segments of the physical world:
- The visual system processes only a narrow range of the electromagnetic spectrum.
- The auditory system is limited to specific frequency ranges.
- Chemical and mechanical sensory modalities are likewise constrained.
Other species extend this range in different directions:
- Bats navigate via ultrasound.
- Bees perceive ultraviolet light.
- Some animals respond to electric or magnetic fields.
These examples do not imply that other species perceive “more reality.” Rather, they demonstrate that each species constructs a specific Umwelt, as classically described in the theory of Jakob von Uexküll.
The key point is:
Perception is not a representation of reality, but a selection from it.
Thus, a deeper layer becomes visible: the so-called “reality” on which scientific observation is based is already a preconfigured experiential world.
4. Science as operation within an already limited world
When scientific research begins, it does not operate in reality “as such,” but in the humanly accessible experiential world.
This implies:
- Measuring instruments extend perception, but only within human interpretative frameworks.
- Data are translations of sensory or technical signals.
- Models are representations of already filtered data.
This leads to a decisive shift:
Science does not merely reduce reality through methods.
It operates within a reality that is already reduced by human perception.
The classical discussion of methodological limitations—sample size, operationalization, measurement error—thus operates on a second level.
Beneath it lies a deeper structure:
the ontological selectivity of the human experiential world itself.
5. The double filter structure: perception and method
A two-layer structure of limitation can be distinguished:
(1) Perceptual filter
The biological and cognitive structure of humans determines what appears as “given” in the first place.
- What cannot be perceived does not enter the data base.
- What cannot be cognitively processed does not exist as scientific input.
(2) Methodological filter
Within this perceptual world, science further selects:
- Operationalization reduces complexity
- Models abstract relations
- Statistics transform continuous phenomena into discrete variables
The result is a double reduction:
Reality → experiential world → data world
Scientific knowledge therefore does not directly access reality, but operates on already pre-structured perception plus methodological transformation.
6. The intuitive but problematic assumption: “That’s obvious”
The claim that humans perceive only a fraction of reality is often considered trivial.
And precisely here lies an epistemic problem.
From the everyday intuition “we do not see everything,” science often implicitly moves to the assumption:
“What we can see and measure is sufficiently representative of what exists.”
This shift usually remains unexamined in research practice, manifesting in:
- the self-evidence of operationalization
- the dominance of measurable variables
- the reduction of complex phenomena to indicators
- the interpretation of data as “objectivity”
This raises a fundamental ontological question:
Is the world discovered by science—or constructed within already limited conditions of perception?
7. Consequences for scientific thinking
If the double filter structure is taken seriously, several consequences follow.
(1) Science describes access-models, not reality itself
Scientific statements become descriptions of reconstructed slices of things within human accessibility.
(2) Objectivity becomes relational rather than absolute
Objectivity is not independence from perspective, but stability within a shared perceptual and methodological space.
(3) Limits of knowledge are structural, not only methodological
Even perfect methods would operate only within the available perceptual space.
This leads to a more radical question:
Are there aspects of reality that are in principle inaccessible to human cognitive structures?
This remains open—but it shifts the focus from measurement error to conditions of access.
8. A cautious re-embedding in scientific traditions
This perspective does not stand outside scientific tradition.
It intersects with central questions in epistemology:
- classical limits of knowledge (Kant)
- structural dependence of scientific observation
- contemporary debates on perspectivity and representation
In modern philosophy of science, it is increasingly acknowledged that data are not simply “given,” but produced through technical, theoretical, and cognitive structures.
The present perspective extends this insight one step further:
Not only are data constructed.
The scientifically accessible world itself is already a construction within human perceptual constraints.
9. Conclusion: The invisible prerequisite of all science
Science does not begin with data.
It begins with perception.
And perception does not begin with reality as a whole, but with a biologically and cognitively constrained interface of what reality could be.
The central insight of this text is therefore not that science is imprecise.
Rather:
Science operates within an already selected experiential world whose boundaries are rarely made explicit.
Methodological limitations are visible.
Ontological limits of method are discussed.
But the limits of perception itself remain largely implicit.
Perhaps this is the deepest form of scientific self-reflection:
not only to ask how well we measure,
but also what is even within the scope of what can be measured—and why.
This perspective extends earlier considerations on methodological selectivity in science by adding a prior question: the structure of human experience itself as the first and most fundamental layer of epistemic limitation.
References and Further Reading
Bennett, M., & Miller, M. E. (2023). The conventionality of real-valued quantities. Philosophy of Science, 90(5), 1338–1350.
Cartwright, N. (1983). How the laws of physics lie. Oxford University Press.
Giere, R. N. (2006). Scientific perspectivism. University of Chicago Press.
Goertz, G., & Mahoney, J. (2012). Concepts and measurement: Ontology and epistemology. Social Science Information, 51(2), 205–216.
Hacking, I. (1983). Representing and intervening. Cambridge University Press.
Kant, I. (1998). Critique of pure reason (P. Guyer & A. Wood, Trans.). Cambridge University Press. (Original work published 1781)
Leonelli, S. (2019). What distinguishes data from models? European Journal for Philosophy of Science, 9(2), 1–21.
McGinn, C. (1991). The problem of consciousness. Blackwell.
Michell, J. (1999). Measurement in psychology. Cambridge University Press.
Nagel, T. (1974). What is it like to be a bat? The Philosophical Review, 83(4), 435–450.
Parker, W. S. (2020). Model evaluation: An adequacy-for-purpose view. Philosophy of Science, 87(3), 457–477.
Popper, K. R. (1959). The logic of scientific discovery. Routledge.
Proctor, A. C. (2022). Calling time. Philosophy Now, (152), 36–38.
Proctor, A. C. (2022). On time, causality, and the block universe. Clink Street Publishing.
Suppes, P. (2002). Representation and invariance of scientific structures. CSLI Publications.
Uexküll, J. von. (2010). A foray into the worlds of animals and humans. University of Minnesota Press. (Original work published 1934)
van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. Oxford University Press.
Vessonen, E. (2021). Representation in measurement. European Journal for Philosophy of Science, 11(76), 1–20.