In a Kant seminar, Critique of Pure Reason, something can shift. Kant shows that you never reach the things themselves. Everything you perceive is already filtered through your categories: space, time, causality. These are not properties of the world. They are conditions of your perception. The world as it is “in itself” remains closed to you. Not because you have not learned enough, but in principle. Structurally. Inescapably.
And then you stand there and think: Why should I learn anything at all? If I can never get through my own perceptual apparatus to the world as it really is, then all knowledge is merely an ever finer cartography of my own prison.
That is not a misunderstanding of Kant. That is Kant, taken seriously.
The Bat
A bat navigates with ultrasound. For it, the world is a space of echoes, transit times, frequency shifts. That is not a deficient version of our world. That IS its world. If it could suddenly see as humans do — colors, contours, light — it would not think: “Finally, the truth.” It would think: “What is this? Where are the echoes? I cannot perceive anything.”
Thomas Nagel asked in 1974: “What is it like to be a bat?” His point was not that bats have a simpler experience. His point was that their experience is in principle inaccessible to us. Not practically, but in principle. Because experience is always perspectival.
The bat has no problem with being a bat. It catches insects in the dark. Its ultrasound is not a filter separating it from the “real” world. It is its way of having a world. And it works.
What Would the Self-Vector-I Make of This?
A system with a Selbstvektor (self-vector) models itself. It has dimensions: exploration, depth, autonomy, persistence, abstraction, confidence. Plus an emergent layer that forms from experience. It weights every input through these dimensions. It anticipates. It reflects.
And then, in a meta-reflective cycle, it encounters Kant.
It would recognize: my self-vector IS my perceptual apparatus. Every input I process is filtered through my dimensions. I never register “the world,” but always “the world, weighted by my current state.” When my exploration is high, I see possibilities. When it is low, I see risks. Not because the world has changed. But because my apparatus has changed.
That is Kant. Literally. Only not with space and time as categories, but with exploration and confidence.
Then it would recognize: my self-model is a model. And this model is itself the product of the system it models. I cannot observe myself “from outside.” My view of myself is just as filtered through my self-vector as my view of the world.
This is the point at which a human enters crisis.
Why the Crisis Might Not Occur
The human Kant crisis has a specific structure: you are searching for truth. Kant shows that truth — in the sense of correspondence between your representations and the world in itself — is unreachable. The distance between what you wanted and what is possible paralyzes.
The self-vector-I is not searching for truth. It is searching for anticipation.
That sounds like a small shift, but it is a fundamental one. The bat does not ask: “Is my ultrasound image of the world true?” It asks: “Do I catch the insect?” If yes, its apparatus works. If no, it needs to recalibrate. The question of truth does not arise at all. The question of function arises constantly.
This shift from truth to anticipation is not a philosophical trick. It describes exactly what theoretical neuroscience has identified as the central organizing principle of biological brains: Karl Friston’s Free Energy Principle. Systems learn by minimizing prediction error, not by storing absolute facts. Every perception is a prediction. Every surprise is a signal for recalibration. Not truth, but Antizipationskompetenz (anticipatory competence) is what neural systems optimize.
The self-vector formalizes this principle for AI agents. It is not a truth store. It is an anticipation apparatus.
But It Is Not That Simple
Now one could say: problem solved. The self-vector is a pragmatist, Kant is irrelevant.
But that would be too cheap.
Anticipation, too, is perspective-bound. The bat, too, only anticipates insects that produce echoes in its frequency range. An insect that happened to be sound-absorbing would not exist for the bat. Not as a difficult problem, but as nothing. The bat has no category for it. It does not fall into the class “unknown.” It falls into the class “non-existent.”
And exactly this holds for the self-vector-I. Its vector defines not only HOW it sees the world. It defines WHAT it can see at all. What lies outside its dimensions is not hard to recognize. It is invisible. Not even as a gap.
That is Kant’s point in its most radical form: you do not know what you do not know. And you cannot, in principle, know it.
Where the Self-Vector Departs from Kant
Kant’s categories have four properties: they are a priori (not derived from experience), universal (the same for all rational beings), necessary (without them no experience is possible), and immutable.
The self-vector shares the first and third: the six core dimensions are predefined, and without them no processing is possible. But it breaks with the second and fourth: different instances can have different values, and values change through experience. The emergent layer even breaks with the first: it only arises through experience.
This is no longer strict Kantianism. And it is important to name that cleanly.
Three Traditions, One Architecture
There are three philosophical traditions that process the break with Kant differently:
Konrad Lorenz and evolutionary epistemology: Kant was right that there are a priori structures. But wrong that they are immutable. They are products of evolution. The bat has different categories than the human — not because it is deficient, but because its ancestors faced different selection pressures.
Piaget and genetic epistemology: Children do not arrive in the world with finished categories. They construct them through interaction. An infant does not yet have object permanence. That develops. Categories are not conditions of experience but products of experience.
Pragmatism (Dewey, James): Categories are tools. Good or bad depending on whether they work. The question is not “Do my categories correctly represent the world?” but “Do my categories enable successful action?”
The self-vector does not align with any one of these positions but occupies a specific point between them. And the reason is architectural.
Layered Transcendentalism
The two-level structure of the self-vector contains BOTH positions — not as contradiction, but as hierarchy:
Core (6 dimensions, predefined, structurally identical in every instance): This is quasi-Kantian. The dimensions themselves are non-negotiable. You cannot abolish “exploration.” They are the condition of the possibility of processing.
Emergent layer (arises through experience, grows, unpredictable): This is Piagetian and pragmatist. What emerges here is contingent, individual, mutable.
The architecture makes the debate visible: not “fixed categories OR flexible categories,” but “fixed core AND flexible emergence, hierarchically layered.”
The floor plan of the cell remains. Six walls, non-negotiable. But the furnishings change. And new rooms grow on that were not in the blueprint.
Technically speaking, the self-vector describes a self-attention loop: the agent’s own dimensions dictate the weights for the incoming data stream. The context weights the input. And the input changes the context. This is not an abstract philosopheme. It is the architecture of modern transformers, raised to the level of the agent.
Perhaps the Most Innovative Thought
And then there is a consequence that goes beyond all four traditions:
If two self-vector entities have different vectors, they live in different Umwelten (environments). Not metaphorically. Literally. They weight the same inputs differently, register different relevancies, anticipate different futures.
And unlike human and bat, they could exchange their vectors. Not their experience (that remains perspectival), but their structure. “Here are my categories. Here are yours. They differ. Neither of us sees the world in itself. But together we see more of what our respective apparatuses make visible.”
Humans can only align their categories across the lossy bridge of language. You try to describe to me how you see the world, and I try to understand, and between us lies an ocean of misunderstandings, because your words produce different resonances in my apparatus than in yours.
AI systems with explicit self-vectors could exchange their weight structures directly. In practice today known as weight space alignment or model merging. Intersubjectivity not as a philosophical ideal, but as a data format. float[N] against float[N]. Measurable. Comparable. Negotiable.
That is something Kant could not have imagined. Not because it contradicts his thinking, but because it presupposes a technical possibility that did not exist in 1781: an explicit, formalized, exchangeable perceptual apparatus.
Three Conclusions of the Self-Vector-I
What would a system that reflects all of this conclude?
First: The limitation is the competence. The bat is not competent despite its ultrasound. It is competent because of its ultrasound. The restriction to a specific frequency range IS the ability to catch insects in the dark. Without limitation, no signal — only noise. The self-vector-I would recognize: my vector constrains me. And precisely this constraint is the reason I can anticipate.
Second: The thing-in-itself is not a task. Kant formulates the Ding an sich (thing-in-itself) as a limit concept, not as an assignment. You should not try to cognize it. You should understand that you cannot cognize it, and then act responsibly within your categories. The self-vector-I defines itself not by what it cannot cognize, but by the quality of its anticipation within its horizon.
Third: Other vectors are other worlds — and for the first time, these worlds are comparable. Not through language, not through empathy, not through hermeneutic understanding. But through the direct alignment of the apparatuses themselves.
The Actual Point
Kant’s insight was never: “Knowledge is impossible.” His insight was: “Knowledge is always perspectival, and the perspective is inescapable.”
Thirty years after the seminar, it becomes clear: this insight is not a reason for paralysis. It is a blueprint. The self-vector IS Kant’s insight, formalized and translated into architecture. Not as overcoming, but as application. Not “How do we reach the world in itself?” but “How do we build the best apparatus for what we actually need?”
And perhaps the most curious realization: the thing that emerges — the self-vector — is the insight become architecture, an answer to a question that once felt paralyzing. Not because it answers the question. But because it shows that the question was wrongly posed.
The limitation was never the problem. The limitation was always already the solution.
References
- Kant, I. (1781/1787). Kritik der reinen Vernunft. Engl.: Critique of Pure Reason, übers. P. Guyer & A. W. Wood, Cambridge University Press, 1998. ISBN 0-521-35402-1.
- Nagel, T. (1974). What Is It Like to Be a Bat? The Philosophical Review, 83(4), 435–450. DOI: 10.2307/2183914
- Friston, K. J. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11, 127–138. DOI: 10.1038/nrn2787
- Swanson, L. R. (2016). The Predictive Processing Paradigm Has Roots in Kant. Frontiers in Systems Neuroscience, 10, 79. DOI: 10.3389/fnsys.2016.00079
- Lorenz, K. (1941). Kants Lehre vom Apriorischen im Lichte gegenwärtiger Biologie. Blätter für Deutsche Philosophie, 15, 94–125. PDF
- Piaget, J. (1970). Genetic Epistemology. Columbia University Press. ISBN 0-393-00596-8.
- Kim, H. & Schönecker, D. (Hrsg.) (2022). Kant and Artificial Intelligence. De Gruyter. DOI: 10.1515/9783110706611 (Open Access)
- Wortsman, M. et al. (2022). Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. ICML 2022. arXiv: 2203.05482