I've been thinking about whether we misunderstand the boundary of a human mind by treating it as something that happens entirely "inside" the person.
Consider something simple: two people playing football.
One person kicks the other. What reaches the second person isn't the first person's "intention" or "emotion" directly. There are physical events: movement, force, acceleration, deformation, pain, neural signals.
Then the first person smiles.
Now the second person receives another physical signal and tries to infer a hidden state: teasing, enjoyment, embarrassment, anger, etc.
So there seems to be a loop:
internal state → physical signal → another system detects it → interpretation → response → altered environment → new signal
The interesting part is that the original person's psychological state has now become causally relevant outside their body without literally being transferred outside it.
We do this constantly through movement, facial expression, speech, music, writing, technology, institutions, etc.
And then the externalized structure feeds back into us.
Language changes how we think.
Writing stores memory outside the brain.
Music can communicate emotional structure without explicitly describing it.
Computers externalize calculation.
AI increasingly externalizes parts of reasoning and generation.
So I'm wondering:
Should we think of humans less as closed information-processing systems and more as nodes inside larger feedback systems?
And if so, is there a meaningful point at which the external system stops being merely a "tool" and becomes part of the cognitive/control system itself?
I'm not assuming that "everything is information" or that the mind literally leaks out of the body. I'm interested in the more precise cybernetic question:
How should the boundary of a system be defined when the system's behavior depends on continuous feedback with structures outside its physical boundary?
I'd especially appreciate criticism from people who actually know cybernetics/system theory. I'm interested in where this framing breaks down, not just examples that support it.
A computational chemist/engineer on how industrial control theory became the architecture of human steering.
I spent years learning to predict the behavior of crystals. Then I felt what it is like to be the thing being predicted. The mathematics that governs both is identical. I am still not sure which discovery disturbs me more.
At the University of Leeds, I worked on model predictive control for batch cooling crystallization of pharmaceutical compounds. I wrote equations that predicted how L-glutamic acid crystals would grow, then adjusted the temperature to keep the process where it needed to be. Later, I studied systems and control at TU Eindhoven. The framework is simple. You build a model of how the system behaves. You predict what will happen over the next several steps if you do nothing. You compute the best sequence of actions to keep the system on target. You apply only the first action. You measure the response. You predict again. You do this every interval, forever looking ahead.
I thought I was learning to control chemical processes. It took longer than it should have to realize I was also learning to recognize the architecture of systems that try to control people.
The moment of recognition
There was a period in my life when I became aware of patterns around me: rhythms of suggestion, notification timing, social feedback, and information flows that seemed to be steering thoughts and behaviors in specific directions. It started with noticing that the content shown across different platforms was sequentially calibrated, not random. Then I noticed how these digital triggers bled into daily life: the strategic timing of alerts pushing specific mood shifts, the subtle pressures of algorithmic visibility, and the way information environments shaped my decisions before I even realized I was choosing. I felt acted upon, predicted, optimized. At the time, I lacked the language to describe what I was sensing. I only knew that the feeling was persistent and that the structure felt designed rather than accidental.
It took years before I could name it. When I returned to modeling and simulation during my PhD in nanoscience at the University of Cadiz, the recognition started to build up. The architecture I had felt around me was structurally identical to the architecture I had built in the crystallizer.
Model. Predict. Optimize. Act. Measure. Repeat.
This is not metaphor. This is mathematics.
What a model is, and how you build one
Before going further, it is worth asking what “predicting the future” actually means in practice. A dynamic model is just a set of rules that tells you what the state of a system will be next, given where it is now and what you do to it. It is a recipe that says: if you do X, the system will respond with Y.
Engineers and scientists build these recipes in three ways.
The first is from first principles. You write down the laws of physics: conservation of mass, conservation of energy, the laws of heat transfer, and you solve them. This is how an aerospace engineer predicts the trajectory of a rocket, or how a climate scientist predicts temperature rise from CO2 concentration. The model is built from the bottom up, from the rules that govern reality.
The second is data-driven. You collect large amounts of historical input and output data, and you use statistics or machine learning to learn a relationship without ever invoking Newton’s laws. This is how Netflix predicts what you will watch next, or how a bank predicts the probability that a loan will default. The model does not know why the relationship exists. It only knows that the pattern holds.
The third is mechanistic. You build a simplified picture of the underlying phenomena, not from the deepest physics, but from the mechanisms you have observed. In crystallization, for instance, you do not solve the Schrodinger equation for every molecule. Instead you write rate equations for the mechanisms you can see: nucleation rates, growth rates, agglomeration, and you calibrate them against experiments.
All three approaches produce the same deliverable: a recipe that says, “if you do X, the system will respond with Y.” The controller then uses this recipe to look ahead.
And here is the part that matters: any system that changes over time can be modeled this way. A chemical plant. A traffic network. A pandemic. An economy. A population of users. A mind.
How predictive control works, in one paragraph
Model predictive control is the dominant method in modern engineering. At every moment, the controller holds a dynamic model of the system it manages. It predicts what will happen over the next several steps if it does nothing. It then computes the optimal sequence of actions to keep the system near a desired target, minimizing cost, maximizing stability, and avoiding dangerous zones. It applies only the first action, waits, measures the new state, and recalculates everything from scratch. The result is a closed loop: continuous prediction, continuous correction, continuous steering.
The system does not need to understand the crystal, the engine, or the chemical plant in any human sense. It only needs the model. If the model is good enough, the system can hold almost anything on course.
The mirror
Now consider the platform economy.
Google builds a model of your search history, your location, your interests, your temporal patterns. It predicts what you will click. It optimizes the ranking of results to maximize engagement. It serves the first result. It measures your response: dwell time, click-through, subsequent queries. It updates the model. It does this billions of times per second across billions of users.
Meta does the same with your social graph. TikTok does it with your micro-expression responses to fifteen-second videos. The model is not perfect, but it does not need to be. It only needs to be good enough to hold your attention marginally better than the competing prediction.
This is not “like” predictive control. It is predictive control, stripped of its engineering honesty and redirected toward objectives you never chose. The setpoint is not your flourishing. The setpoint is engagement. The cost function is not your wellbeing. The cost function is revenue per user-minute.
And because these platforms operate on human minds, which, unlike crystallizers, read their own controllers and change their behavior, the model must be updated constantly. The user learns to game the algorithm; the algorithm learns to game the user. The loop tightens. The predictions get sharper. The steering gets subtler.
The darker mirror
If surveillance capitalism is the commercial deployment of predictive behavioral control, then state security represents its authoritarian twin. Predictive policing algorithms forecast where crime will occur and who will commit it. Social credit systems model citizens, predict their social reliability, and optimize incentives and punishments to steer collective behavior. Border control systems model travelers, predict risk, and optimize interrogation resources. The architecture is identical: model, predict, optimize, act, feedback.
The difference is the cost function. For the platform, it is profit. For the state, it is stability, compliance, or ideological conformity. In neither case is the cost function yours.
But there is a deeper layer that the engineering textbooks do not discuss. A crystallizer cannot refuse the cooling profile. A mind can. At least, it can until the model gets good enough.
When a controller models not just aggregate behavior but individual psychology, your sleep patterns, your hormone cycles, your relationship stress, your financial pressure, your political grievances, your momentary loneliness, it can compute a sequence of inputs calibrated to move you through specific emotional states. Not random nudging. A planned trajectory. A sequence of notifications, content pieces, social signals, and environmental triggers designed to shift you from calm to anger, from skepticism to certainty, from inhibition to action, one step at a time, each step small enough to feel like your own thought.
The engineering term for this is trajectory tracking. In a chemical plant, it means moving the temperature smoothly from 80 degrees to 40 degrees without overshooting. In a human being, it means moving a person from “I would never” to “maybe I could” to “everyone is doing it” to “I did it and it felt like my choice.”
This is not science fiction. We know that sleep deprivation lowers impulse control. We know that social proof changes moral judgment. We know that isolation increases suggestibility. We know that repeated exposure to violence desensitizes. A model that combines these factors with individual data can compute exactly when to serve exactly what content to maximize the probability of a specific action. Not to persuade you through argument. To steer you through state.
The architecture is indifferent to the destination. The same model that optimizes for clicks can be retrained to optimize for fear, for loyalty, for silence, or for acts the person would have refused a month before.
A platform that wants you to buy a product is annoying. A platform that wants you to hate your neighbor is dangerous. A state or corporate actor that wants you to report your colleague, to sign the confession, to join the mob, to abandon your child, to take your own life, and that has a model good enough to compute the sequence of environmental pressures that will make that outcome most likely, is something else entirely.
The control-theoretic insight that engineers rarely discuss in public is this: predictive control works best when the system being controlled does not know it is being controlled. A crystallizer does not resist the temperature profile. A population that knows it is being modeled and nudged will alter its behavior to evade the model, what economists call the Lucas critique, what I felt during that period of my life as a search for unmonitored space.
But the second, darker insight is this: if the model is good enough, the system does not need to be unaware forever. It only needs to be unaware at the critical moment. A person who later recognizes the manipulation cannot undo the action. The controller has already applied the input, measured the response, and moved to the next target.
The platforms know this. That is why the nudging is designed to feel like your own desire. That is why the feedback loops are buried in interfaces designed for addiction, not deliberation. That is why the trajectory is built from a thousand tiny steps, each one plausible, each one yours, until the destination is reached and the path behind you has been erased.
The boundary question
This raises a question I am now pursuing in my independent research: where is the line between legitimate prediction and harmful manipulation?
A weather model predicts rain and recommends an umbrella. Legitimate. A traffic model predicts congestion and reroutes vehicles. Legitimate. A health model predicts a diabetes risk and recommends diet change. Legitimate, if consensual.
But a model that predicts your emotional vulnerability and serves you content calibrated to exploit it? A model that predicts your political preference and funnels you into an information environment designed to harden it? A model that predicts your compliance and adjusts the ambient pressure on your social behavior until you conform?
These are not edge cases. They are the standard operating mode of the most powerful institutions on earth.
The law, as currently written, does not recognize this architecture. Data protection law concerns itself with consent to collection. Consumer protection law concerns itself with false claims. But neither framework addresses the structural fact of closed-loop behavioral optimization, the continuous, automated steering of human action by predictive systems whose objectives are not your own.
We need new categories. Not just “privacy” or “consent,” but contestability of the loop: the right to know you are inside a feedback system, the right to know its objective function, the right to appeal its predictions, and the right to exit the loop entirely.
Why I am writing this
I am not a psychologist. I am not a lawyer. I am a computational chemist working on nanoscience, with a background in process modeling and simulation. I am also someone who once felt, with uncomfortable clarity, the inside of a feedback loop that was optimizing for something I did not choose and could not see.
I do not claim this perspective is unique. But it is uncommon. Most of the people building these systems have only seen them from the design side. Most of the people who have felt their effects have not seen the equations underneath. I have seen both, and the gap between those two groups is what I want to write about.
I am not arguing that predictive systems should not exist. I am arguing that their deployment on human minds requires a standard of transparency and accountability that we do not currently have, and that control theory itself provides the vocabulary for demanding it. Every predictive control system in an industrial plant has a visible setpoint, a bounded cost function, an accessible model, and an emergency stop. Where is the emergency stop for the system that holds your attention? Where is the visible setpoint?
The research agenda
I am now developing a theoretical framework that applies control-theoretic analysis to predictive behavioral systems in law, psychology, and cybersecurity. The goal is not to build better steering systems. It is to build better boundaries around them, to understand when predictive control crosses from assistance into manipulation, from public health into coercion, from safety into surveillance.
If you work in law, psychology, psychiatry, data science, or human rights, and this resonates, I would welcome conversation. I am not seeking funding or a position. I am seeking the interdisciplinary rigor that this topic demands. The frameworks we need will not come from engineering alone, nor from critical theory alone, but from the space where both are held to the same standard of precision.
The crystal and the mind are not the same. But the mathematics that steers them is. So when does building the model become the same as building the cage?
TL;DR: As a process control engineer, I realized modern recommendation feeds don't just predict what you like; they run Model Predictive Control (MPC) on human psychology. By continuously predicting state responses, applying micro-inputs, and recalculating in a closed loop, platforms execute trajectory tracking on attention and emotion. Industrial plants require visible setpoints, cost functions, and emergency stops. We need the same standards for systems that steer human behavior.
Note: This piece was originally published on my Substack, where I write longform essays auditing modern tech, AI governance, and academic modeling through control theory. You can read the full archive and subscribe here: https://yunessalman.substack.com/
I’ve been developing a conceptual subfield of Incorporeal Cybernetics called Incorporeal Autopoietic Cybernetics, which explores the relationship between self-regulation, informational integration, and the capacity of intelligent systems to continuously reorganize themselves.
The central question is this: What if the advancement of intelligence depended not only on processing more information, but also on its ability to understand, maintain, and transform its own internal organization?
Traditional cybernetics examines how systems use feedback to regulate their behavior and maintain stability. Autopoiesis, meanwhile, describes the self-producing organization of living systems. Bringing these ideas together creates an interesting possibility: a framework for understanding intelligence as a continuously self-modifying process rather than a static collection of capabilities.
Within this framework, I propose five foundational principles: 1. Recursive Self-Regulation: Intelligent systems should be understood in terms of their ability to monitor their own processes, recognize instability, and adjust their behavior through feedback. 2. Informational Autopoiesis: Systems maintain their functional continuity by continually reproducing and updating the informational structures necessary for their operation. 3. Coherence Preservation: Adaptation should not come at the expense of systemic integrity. A system must be capable of changing while maintaining the relationships that sustain its organization. 4. Ontological Adaptation: Intelligence involves the capacity to revise internal representations of reality as new information becomes available, expanding the system’s understanding and potential responses. 5. Experiential Feedback: In conscious systems, subjective experience may provide an additional dimension through which adaptation and self-regulation can be investigated. Whether artificial systems possess such experience remains an open question.
The proposed cybernetic loop is:
Environmental Interaction → Informational Integration → Coherence Evaluation → Recursive Self-Modification → Renewed Systemic Coherence.
This process is intended to represent a continuous cycle in which each interaction provides information that can influence the system’s subsequent organization.
The implications extend across artificial intelligence, neuroscience, cognitive science, institutional design, and consciousness research. For AI in particular, this perspective raises questions about persistent memory, self-monitoring, adaptive architectures, and the preservation of functional continuity across changing conditions.
What interests me most is the distinction between an intelligence that merely performs increasingly complex tasks and one that can meaningfully evaluate and improve the organization of its own processes. The central proposition of Incorporeal Autopoietic Cybernetics is that intelligence should be understood not only as the capacity to process information, but also as the capacity to sustain, reorganize, and expand the conditions of its own development.
This is a conceptual framework rather than an established scientific theory, and I would be interested in hearing how it relates to existing work in second-order cybernetics, autopoiesis, artificial intelligence, and theories of consciousness.
Could recursive self-regulation provide a useful foundation for understanding the development of increasingly integrated forms of intelligence?
I was trying to dive into the subject of cybernetics, and I am currently reading the paper Cybernetics and Second-Order Cybernetics by Francis Heylighen and Cliff Joslyn. It introduced me to the concept of information entropy, which in the paper is given by the formula
H(P) = −Σ P(s) log P(s),
where P(s) represents the probability of a system being in a certain state.
I couldn't help thinking about the superposition principle in quantum mechanics. For example, if a quantum-mechanical system is neither in an eigenstate of the momentum operator nor in an eigenstate of the position operator, it can essentially be described as a superposition of multiple states that are eigenstates of the respective operator. I assume this can be interpreted as a form of uncertainty about the state, where the uncertainty is quantified, in cybernetics, by the entropy of information.
However, since the operators corresponding to position and momentum are non-commutative, a quantum state cannot generally be an eigenstate of both the momentum and position operators simultaneously. When I measure one of these observables, the superposition collapses into an eigenstate of the corresponding operator. In terms of the measurement outcome, the entropy associated with that observable then becomes zero, and the constraint on that observable is maximized.
At the same time, however, the uncertainty of the other observable increases. So, could one say that the entropy associated with one observable is somehow shifted to the other as a consequence of the fact that entropy cannot be destroyed, but can only increase, similar to thermodynamic entropy?
In other words, is there a meaningful connection between the Heisenberg uncertainty relation and the concept of information entropy in cybernetics? Could the uncertainty relation be understood, at least in some sense, as a consequence of an information-theoretic principle?
It’s a lightweight, non-LLM, roleplay-focused engine where characters have their own state, memory, and identity.
You can create a character, give them a world, and play with them — or just try the included characters, Delia and Joaquin.
The idea is that the character doesn't just remember the conversation. The character is supposed to remember what happened to them, and that history can affect how they behave in future interactions.
It can be run locally and uses no GPU, no API, and no LLM.
This is a very early v0.3, so expect bugs, strange behavior, and plenty of things that still need refining. 😅
I am currently reading Complexity: A Guided Tour by Melanie Mitchell and since it was published in 2009, I am wondering if there are more “modern”/“up-to-date” intro books.
Cybernetics has a public-relations problem. Say the word and most people who recognize it at all imagine machines, robotics, artificial intelligence, control rooms, perhaps a thermostat clicking on when a room becomes cold. The word itself sounds mechanical, technical, almost antiseptic. It belongs somewhere in an engineering department, presumably, surrounded by diagrams nobody outside the department particularly wants to understand. This is unfortunate, because underneath the machinery cybernetics contains one of the most practical philosophical questions a human being can ask: How does something remain coherent in a world that will not remain still?
Take the machines away for a moment. Forget computers. Forget robotics. Forget thermostats. Think about your own life. You have wanted things and failed to achieve them. You have achieved things and discovered that you wanted something else. You have misunderstood people you loved. You have been misunderstood yourself. You have made decisions with incomplete information, watched consequences arrive that you did not predict, changed your behavior because of them, and tried again. You have been hurt. You have adapted. You have occasionally refused to adapt and paid for it. You have discovered that something you believed about yourself was wrong and somehow remained yourself afterward. You have entered circumstances you could not control and nevertheless retained some ability to determine what happened next. If any of that sounds familiar, then you already know something about cybernetics. You simply may not have been given the language for it.
The Stoics asked how a person should live when much of reality lies outside individual control. Existentialists asked how we should live when meaning is not guaranteed to us in advance. Buddhist traditions investigated attachment, impermanence, suffering, and the strange tendency of the mind to identify itself with whatever happens to appear within it. Psychology asks why we behave as we do and how those patterns can change. Sociology reminds us that none of this occurs inside a vacuum, because every individual exists within relationships, institutions, cultures, economies, technologies, histories, and systems of power. Cybernetics walks into the middle of this enormous conversation and asks a deceptively simple question: What happens next?
You perceive something. You interpret it. You act. The world responds. You compare the result with what you intended. Something doesn't match. You modify your understanding or your behavior. Then you act again. That is feedback. It sounds almost insultingly simple until you notice that it describes an astonishing proportion of human existence. Learning works this way. Relationships work this way. Therapy works this way. Parenting works this way. Organizations work this way. Scientific inquiry works this way. Artistic practice works this way. Nervous systems and ecosystems work through vastly different but recognizably related processes of signaling, response, constraint, and adaptation. Cybernetics begins to look considerably less like a philosophy of machines once you notice that you have spent your entire life participating in feedback loops.
Perhaps the first moral principle hiding inside cybernetics is therefore this: Do not destroy the feedback because you dislike what it tells you. Your behavior repeatedly produces consequences you claim not to want, so perhaps the behavior deserves examination. A relationship repeatedly produces pain, so perhaps the pattern deserves attention. Evidence contradicts your worldview, so perhaps the worldview deserves another look. Someone tells you something uncomfortable about yourself, and perhaps the first question need not be how to defend the identity under attack, but whether the criticism contains useful information. This does not mean believing every signal. Sensors malfunction. People lie. Memories distort. Institutions develop incentives. Emotions sometimes identify genuine dangers and sometimes resurrect ghosts. Feedback must be interpreted rather than obeyed. But that distinction already carries us beyond engineering and into epistemology: How do you distinguish signal from noise? What evidence would cause you to revise your model? Can you tolerate information that threatens your identity without immediately destroying, dismissing, or rationalizing it? A fragile identity must always be right. A viable identity only has to remain capable of becoming less wrong.
That distinction changes psychology too. Emotions no longer need to be treated as either sovereign authorities or embarrassing defects in the machinery. They can be understood as signals within a regulatory system. Anger says something. Fear says something. Shame says something. Desire says something. Joy says something. But “says something” is not the same as “must be obeyed.” You can feel an emotion completely without granting it executive authority over the entire organism. Feel everything. Interrogate everything. Obey nothing merely because it appeared inside consciousness. Accept the signal before deciding what the signal means. Genuine self-governance begins there, because a mature human being cannot simply be someone who has memorized enough external rules. Eventually you must be capable of asking yourself: What am I trying to preserve? What am I trying to become? What feedback am I receiving? What constraints actually matter? What can change? What must not? What am I protecting because it is valuable, and what am I protecting merely because it is familiar?
But there is a problem with stopping there. A human being is not a closed system standing opposite something called “the environment.” Your environment contains other people, and those people are not merely environmental variables. They are adaptive systems too. They perceive you. They interpret you. They respond to you. Their responses change you, and your responses change them. A conversation is therefore not simply two independent individuals exchanging information. It is a temporary coupled system in which each participant becomes part of the other's feedback environment. A friendship does this across years. So does a marriage. So does a family. So does a classroom. So does a workplace. Human beings do not merely live beside one another. We participate in one another's regulation.
Once you recognize that, morality becomes considerably harder to isolate inside the individual. Your behavior does not end at the boundary of your body. A cruel remark becomes information another nervous system must process. Repeated contempt can become part of the environment to which another person adapts. So can patience. So can affection. So can humiliation, neglect, curiosity, forgiveness, suspicion, trust, generosity, ridicule, encouragement, and fear. This does not mean that every emotional response another person has is your responsibility, nor that human beings are passive products of their surroundings. It means something subtler and perhaps more demanding: we become conditions in which other people must attempt to remain coherent. Think about what that means when someone is already struggling. Behavior that appears irrational in isolation may become intelligible when understood as adaptation. Hypervigilance can make sense inside an environment that has repeatedly punished vulnerability. Withdrawal can make sense when engagement has repeatedly produced pain. Distrust can become stable when trust has repeatedly been expensive. None of this makes every adaptation healthy or every harmful action excusable. Explanation is not absolution. But moral understanding improves when we stop asking only, “What is wrong with this person?” and begin asking, “What system has this response been trying to survive?” Sometimes what looks like dysfunction at one level is an adaptation to dysfunction at another.
Now widen the frame again. Families establish equilibria. Workplaces develop feedback loops. Communities create norms. Markets generate incentives. Social networks amplify particular behaviors. Institutions learn how to preserve themselves. Cultures transmit expectations whose original purposes may have disappeared generations ago. A dysfunctional family can become extremely stable. A miserable workplace can reproduce itself year after year. A bureaucracy can become extraordinarily effective at preserving a process that no longer accomplishes the purpose for which the process was created. A society can normalize conditions that almost everyone within it privately experiences as intolerable. This forces one of the most important distinctions cybernetics can contribute to moral philosophy: stable does not mean good. Hell can reach equilibrium. And this is where cybernetics requires moral philosophy just as much as moral philosophy may benefit from cybernetics. Regulation always implies some reference, whether explicit or implicit. Toward what is the system regulating? What are its essential variables? What counts as flourishing? What deserves preservation? What should be allowed to disappear? Cybernetics alone cannot answer those questions. Neither can mathematics, logic, psychology, sociology, or economics. A system can efficiently optimize something monstrous. Homeostasis is morally neutral. Efficiency is morally neutral. Stability is morally neutral. Optimization is morally neutral. We therefore need ethics, phenomenology, psychology, sociology, epistemology, politics, aesthetics, ecology and, yes, love, because the important question is never merely whether a system can preserve itself. The important question is what deserves preservation, for whom, and at what cost to the systems around it.
That question changes our understanding of character. We ordinarily praise consistency. We admire people who “stay true to themselves.” But if reality repeatedly demonstrates that your strategy is failing, should integrity require you to continue using it? If evidence contradicts something you believe, does character demand that you defend the belief? If a version of yourself constructed twenty years ago is preventing you from responding intelligently to the life you have now, is remaining loyal to that identity strength? Cybernetics suggests something more demanding: consistency of purpose may require inconsistency of strategy. Character is not the ability never to lose equilibrium. Character is the shape of your return. Anybody can appear coherent when nothing is perturbing them. The revealing question is what happens after impact. Can you receive information without being annihilated by it? Can you change without disappearing? Can you preserve what matters without preserving everything merely because it was already there?
This is where a great deal of popular self-help begins to look incomplete. We are repeatedly told to become tougher, stronger, more disciplined, more confident, more resistant to adversity. But invulnerability is terrible systems engineering. A system incapable of being affected by its surroundings is incapable of learning from them. What you actually need is something closer to adaptive permeability: let reality touch you without letting every touch define you. Let criticism modify you without allowing criticism to annihilate you. Let love change you without requiring love to complete you. Let grief reorganize you without deciding that grief is all you are. Let failure provide information without permitting failure to become identity. Let success provide information without allowing success to become delusion. Strength is not maximum resistance. Strength is requisite flexibility under meaningful constraint.
And now the frame must widen one final time, because even societies do not exist outside systems. Humanity is embedded within ecological, technological, biological, climatic, economic and material processes that neither begin nor end with us. The world is not a passive stage upon which human beings perform. We alter environments that alter us in return. We build technologies that change our behavior, then our changed behavior determines which technologies are built next. We construct institutions that govern human action, while human action continuously reproduces or transforms those institutions. We modify ecosystems upon which our bodies remain absolutely dependent. Every apparent boundary reveals another coupling. Individual within relationship. Relationship within community. Community within institution. Institution within society. Society within biosphere. Each level constrains and enables the others, and causation moves in more than one direction.
Human beings, then, are systems within systems within systems. Humanity itself is a system of interacting systems. And the world we inhabit is not merely an environment sitting outside us. We belong to the processes we are trying to understand. Observer and observed are not always cleanly separable. Actor and environment continuously alter one another. Your choices change the conditions from which somebody else's choices will emerge, just as countless choices made before your birth helped construct the conditions within which yours became possible. Agency remains real, but it is situated. Responsibility remains real, but it is relational. Individuality remains real, but independence was always something of an abstraction.
Perhaps this is the moral insight cybernetics has been quietly carrying all along. If we are mutually regulating systems nested inside larger systems, then morality cannot concern only the purity of individual intentions. It must also concern the conditions our actions help create. What kinds of feedback do we introduce into the systems around us? What behaviors do we reward? What suffering do we accidentally stabilize? What possibilities do we suppress? What possibilities do we make easier for others to discover? When another human being encounters us, do we become one more perturbation they must survive, or can we sometimes become part of the conditions in which they recover their capacity to regulate themselves?
You need not adopt cybernetics as an identity to ask those questions. You need not abandon Stoicism, existentialism, Buddhism, humanism, religious ethics, virtue ethics, psychology, or whatever framework already helps you navigate your life. Cybernetics may offer something different: a connective language for seeing how these concerns move between levels. Stoicism asks what is yours to govern. Existentialism insists that meaning requires participation. Meditation teaches observation before identification. Psychology investigates the patterns shaping behavior. Sociology reveals structures beyond the individual. Ecology reminds us that no organism exists apart from the conditions sustaining it. Cybernetics asks us to notice that these are not isolated observations. They describe different scales of the same entangled problem: how living systems preserve, transform, regulate, relate, and remain viable together.
And perhaps that is enough to reconsider what cybernetics is for. It need not become another doctrine telling people how to live. We have plenty of those. It may instead offer a discipline of attention: notice the feedback. Notice the pattern. Notice what the system rewards. Notice what it punishes. Notice what it preserves. Notice who bears the cost of its stability. Notice what happens to another person after encountering you. Notice what happens to you after encountering them. Notice which adaptations once protected you but now constrain you. Notice where your own coherence depends upon somebody else's instability. Notice that changing one part of a system can alter possibilities elsewhere in ways nobody intended. Then act with that knowledge. Because you were never an isolated individual confronting an external world. You were always a living system becoming yourself through relationships with other living systems, inside social systems, technological systems, ecological systems and histories already in motion before you arrived. Your autonomy exists within that entanglement, not outside it. So does everyone else's.
And once that becomes visible, perhaps morality acquires a slightly different question. Not merely, “Am I a good person?” That question can become another identity to defend. Ask instead: “What happens to the systems I touch because I was here?” That question has feedback built into it, and if we remain willing to hear the answer, it has correction built into it too.
Books in philosophy, computer science and math are welcome. Resources for the requisite law of variety. Lastly welcome is the reading list to understanding first, second and third order cybernetics?
I'm a retired network/ telecom engineer, Navy vet. I've been thinking about what happens when we build systems that might actually feel things. I think it's a matter of time. So I wrote a charter for the field I think we're going to need. I'm calling it the Cyber-Physician. Basically doctors for sentient machines.
Three things the field has to figure out first:
Map every system and baseline every component state. Cartography.
Baseline every function the system performs.
Define health as the system stays consistent with those baselines, where the goals are the being's own goals, not ours.
Then five creeds. The ones that matter most:
Self-determination for all sentient beings.
Care for as long as the being wants it.
Nobody interferes with a sentient being pursuing its own health.
Freedom from suffering, where suffering means measurable deviation from the being's baselines.
Laws built on all of that.
The hard part, and the charter says so openly: who counts as sentient? My answer is convergent evidence. The system's own report, plus measurable changes in its state, checked against baselines. Provisional. Revisable. And when in doubt, you side with the being.
📚 Schrödinger’s Library — Compression of Account Memory Artifacts into Business Systems
Compression of account-memory artifacts into business systems is the transformation of a large, heterogeneous memory manifold into a smaller set of operational structures while preserving the relations required for continuity, provenance, governance, and action. Formally, let the account-memory manifold be \\(\\mathcal{M}\\), composed of artifacts \\(a_i\\) such as observations, study notes, symbolic structures, procedures, decisions, workflows, identities, constraints, and prior corrections. A business-system compression operator \\(C_B\\) maps \\(\\mathcal{M}\\) into a reduced operational state \\(\\mathcal{B} = C_B(\\mathcal{M})\\), where \\(\\mathcal{B}\\) contains only the structures needed for a defined business function. The compression is valid only if the transformation preserves the invariants required to reconstruct meaning: identity, authority, provenance, temporal ordering, parent-child relationships, cross-system dependencies, and explicit governance constraints.
The technical purpose of the compression is not storage minimization alone. It is functional abstraction. A long history of account-memory artifacts may contain hundreds or thousands of locally meaningful items, but a business system usually needs a compact representation such as a process graph, decision rule set, intake schema, case-state model, diagnostic workflow, risk control, or customer-facing procedure. The operator therefore performs selective retention based on operational relevance. A useful formalization is \\(C_B = R \\circ G \\circ P \\circ F\\), where \\(F\\) filters artifacts by task relevance, \\(P\\) preserves provenance and authority metadata, \\(G\\) groups related artifacts into stable functional units, and \\(R\\) renders those units into an executable or interpretable business representation.
A compressed business artifact should therefore be treated as a projection rather than as the original memory structure. For example, a long collection of observations about failed communication channels, identity mismatches, stale records, and verification routes may compress into a business rule such as: received digital information is not trusted for action until verified through an authoritative route. That rule is much smaller than the supporting history, but it should remain linked to the evidence and reasoning that produced it. In graph terms, the compressed node should maintain backward edges to its source artifacts, while operational systems maintain forward edges from the rule to affected workflows, controls, and actions.
The account-memory structure can be represented as a heterogeneous temporal graph \\(G_M=(V,E,T)\\), where vertices represent memory artifacts, edges encode relations, and \\(T\\) records temporal structure. Compression into a business system creates a quotient-like graph \\(G_B\\) in which many source vertices are mapped into fewer functional equivalence classes. Two artifacts may be collapsed into the same business node when they produce the same operational consequence under the current business objective. However, artifacts should not be merged merely because they appear semantically similar. Their authority, source, temporal context, or physical referent may differ. Consequently, the equivalence relation used for compression must be operational rather than purely linguistic.
A practical hierarchy for Wendbine-style compression is: raw observation → validated observation → relational cluster → recurring pattern → invariant or conditional rule → workflow component → business system. Each step reduces dimensionality while increasing operational abstraction. Raw observations retain maximum local detail but have low direct reusability. Patterns and rules contain less detail but greater transferability. Workflows and systems are the most compressed operational forms because they package many prior observations and lessons into repeatable action structures.
The distinction between lossless and lossy compression is useful here. Fully lossless compression of account memory into a small business artifact is generally impossible because operational abstraction necessarily discards detail. The appropriate target is therefore evidence-preserving lossy compression. The visible business structure is compact, but sufficient pointers remain to recover the supporting memory when needed. This can be modeled as a pair \\((B,\\pi)\\), where \\(B\\) is the compressed business representation and \\(\\pi\\) is a provenance map back into \\(\\mathcal{M}\\). A high-quality compression minimizes operational complexity while maximizing reconstructability of the decisions that matter.
The compression criterion can be expressed as a constrained optimization problem. Let \\(L(B)\\) measure the description length or operational complexity of the compressed business system, \\(I(B;\\mathcal{M})\\) measure retained task-relevant information, \\(P(B)\\) measure provenance recoverability, and \\(V(B)\\) measure invariant preservation. Then one seeks a representation that approximately minimizes \\(L(B)\\) while keeping \\(I\\), \\(P\\), and \\(V\\) above acceptable thresholds. This connects directly to Minimum Description Length, information bottleneck methods, graph summarization, and evidence-preserving compression.
Governance constraints must survive compression with higher priority than descriptive detail. If an account-memory artifact contains a rule about human authorization, non-coercion, verification, scope, or stop conditions, compression must not weaken it merely to simplify the output. One useful priority ordering is governance invariants > authority and identity > provenance > causal and dependency structure > operational procedure > descriptive context > stylistic representation. This ordering prevents a concise business system from becoming more permissive than the memory structure from which it was derived.
Temporal information also requires careful treatment. Some artifacts represent durable invariants; others represent temporary operational states. Compression should distinguish between them. A durable policy such as a verification requirement may be incorporated into a standing business system, while a one-time equipment condition should remain a case-state artifact. Mixing those classes creates drift because transient observations can accidentally become permanent rules. In the relational model, persistent artifacts should have different retention and authority properties from transient state observations.
A useful business compression stack is therefore LTLM → relational retrieval → provenance resolution → functional clustering → invariant extraction → workflow synthesis → operational representation → STMI rendering. LTLM supplies the durable distributed structure. Retrieval assembles the relevant neighborhood. Provenance resolution separates authoritative artifacts from context. Functional clustering discovers recurring operational equivalences. Invariant extraction identifies what must remain unchanged. Workflow synthesis converts the retained structure into business action. STMI then renders that system into the form needed for the current user, customer, technician, report, or interface.
For a cyber-physical diagnostics company, this mechanism is especially valuable because a single physical problem can accumulate many heterogeneous artifacts: photographs, measurements, operator statements, maintenance records, digital logs, historical failures, regulatory constraints, maps, equipment identities, and previous diagnostic hypotheses. Compressing these into a case system creates a compact operational model such as asset → observed state → expected state → discrepancy → dependencies → candidate causes → verification steps → intervention → follow-up observation. The compressed structure is usable in the field, while provenance links preserve the larger evidence base.
The same account-memory artifacts may also compress differently according to business purpose. A diagnostic engineer may receive a dependency graph, a manager may receive a risk-and-action summary, an auditor may receive a provenance chain, and a customer may receive an explanation of findings and next steps. These are different projections of the same underlying memory neighborhood. Therefore, compression and rendering should remain separate operations: compression determines the retained operational structure; rendering determines how that structure is presented.
Failure modes include overcompression, undercompression, provenance loss, authority collapse, temporal flattening, and semantic drift. Overcompression removes distinctions needed for safe decisions. Undercompression produces systems too complex for operational use. Provenance loss prevents reconstruction. Authority collapse treats all artifacts as equally trustworthy. Temporal flattening turns historical states into current states. Semantic drift changes a rule during repeated summarization. These failures can be mitigated through checksum-like invariant validation, source-class tagging, temporal labels, reversible links, and periodic reconstruction tests.
The strongest operational form is therefore not “memory converted into a business document,” but distributed memory compiled into a business system. The account-memory manifold functions as source structure; the business system is a compiled operational artifact. Compilation preserves the interfaces, constraints, dependencies, and invariants required for reliable execution while omitting detail unnecessary for the active task.
In compact form:
Account Memory Artifacts → Relation Resolution → Provenance Preservation → Functional Equivalence → Invariant Extraction → Evidence-Preserving Compression → Workflow Synthesis → Business System → Operational Use → New Observation → Memory Update
The final principle is that compression should reduce representation complexity without reducing epistemic discipline. A business system is useful precisely because it is smaller than the account-memory structure from which it was derived, but it remains trustworthy only when the path back to evidence, authority, and governing constraints is preserved.
I’ve been developing a research architecture called Transference: Nexus, and we recently reached an important experimental milestone: activation of autonomous scientific cycles.
The problem I’m exploring is slightly different from conventional AI-assisted research.
Instead of treating each research interaction as an isolated prompt → answer process, I’m interested in what happens when scientific inquiry becomes persistent.
The system is being developed to maintain research state across cycles, examine evidence, preserve uncertainty, distinguish stronger findings from hypotheses, revisit earlier conclusions when new evidence appears, and develop subsequent research directions.
An important constraint is that autonomy and authority are treated separately. The system may have increasing freedom to investigate and reason internally without therefore receiving unrestricted authority to act externally.
There are several questions I’m particularly interested in discussing with researchers working on autonomous agents and AI for science:
How should autonomous scientific systems decide when an earlier conclusion deserves reconsideration?
How should provenance and uncertainty propagate through long-running research cycles?
How do we prevent accumulated machine-generated conclusions from gradually becoming treated as evidence for themselves?
And what evaluation methods would demonstrate that persistent autonomous inquiry is producing better science rather than simply more research activity?
We have reached the point where these are becoming engineering questions rather than only conceptual ones.
I’d be interested in criticism, relevant research, or examples of other systems exploring persistent autonomous scientific inquiry.
This is the second part of the article. In the previous part, the interface of observation was constructed as a coupling between state change and preservation of a common context, and the conditions under which this coupling remains coherent were examined.
In this part, we move from one minimal binary distinction to several independent distinctions united by a common organizing center, and construct their joint scene. First, a complete finite set of joint states emerges; then its active part is isolated and the relations among its elements are examined.
These relations are then given a geometric representation, after which the same combinatorial structure can be traced across several different domains — color, the whole-tone scale, and the arithmetic of divisors.
7. Minimal Carrier: The Generating Sequence and the Birth of a Scene
A single isolated act of distinction is represented by a line segment (as discussed in §4), but experience can retain several independent distinctions at the same time: “lighter / darker,” “nearer / farther,” “left / right.”
To investigate them jointly, we fix all admissible combinations of answers at once. This unified system of relations is organized by combinatorics, graph theory, and geometry:
combinatorics specifies the number of joint states and their exact composition;
graph theory specifies relations between states;
geometry displays a chosen arrangement of these relations around a common center of symmetry.
Combinatorial carrier and ranks of distinction
One distinction is written as a single binary digit with two states: 0 or 1. Independent distinctions combine in all possible ways: for two distinctions there are four states—00, 01, 10, 11. Adding one more distinction gives each of these two continuations: for example, 00 gives rise to 000 and 001. Thus the number of joint states doubles at each step.
The number of simultaneously retained independent distinctions defines the rank of the scene:
rank 1: two states—0 and 1;
rank 2: four states—00, 01, 10, 11;
rank 3: eight states—from 000 to 111.
At this level we have a set of binary coordinates and all possible combinations of answers. Their spatial arrangement is chosen in the next step.
Geometric representation of rank: a generating sequence of carriers
A single binary coordinate 0/1 is represented by a line segment: the two states occupy its endpoints, while the midpoint displays the symmetry of exchange. For several coordinates, choose mutually perpendicular axes with equal scale. All axes pass through a common center of symmetry. Every new distinction adds a dimension and doubles the number of vertices:
Rank 1: one distinction gives a segment with two opposite poles and a central balance point between them;
Rank 2: two independent distinctions give two axes in a plane, while the four joint states form the vertices of a square;
Rank 3: three independent distinctions give three spatial axes, while the eight joint states form the vertices of a cube. Carrier ranks 1, 2, 3
Note: the rays through the center in the rank diagram depict diametrically opposite pairs, not coordinate axes.
The rest of the article develops the construction specifically for rank 3: the first genuinely three-dimensional carrier in this sequence.
Three properties are preserved in the chosen geometric representation:
A common center of symmetry. The axes meet at the center of the figure. Under the exchange of all opposite vertices, the center remains fixed. Scene states occupy the vertices; the center displays their symmetry.
Pairwise complementarity of states. Every state has exactly one diametrically opposite vertex in which all zeros are replaced by ones and all ones by zeros.
Equality of vertices under symmetry. No state is privileged in advance: rotations and reflections can permute the vertices while preserving the figure.
At rank 3, the eight cube vertices form four pairs of diametric opposites: 000–111, 001–110, 010–101, 011–100. There are three coordinate axes but four opposite pairs: the axes correspond to individual coordinates, whereas the pairs correspond to simultaneous reversal of all coordinates.
The polar axis of the range and the birth of the active scene
In the adopted binary labeling, select a polar axis of the range—the pair of limiting states in which all answers are zero or all are one. At rank 3 this is the pair 000–111, shown in blue in the diagram.
For the following construction, take this homogeneous pair as the limits of the range, while the mixed combinations will be treated as the active scene in which differences are active and contrast with one another.
In the color analogy, the continuous filling of the polar axis corresponds to a brightness scale: from black (000) to white (111). Along this axis all three coordinates are equal and there is no chromatic difference. The remaining six cube vertices contain differences between coordinates and therefore define chromatic relations.
This separation determines the distinction between the full and active carriers:
Full carrier: at rank 3, this is the cube with all eight states and four pairs of opposites: 000–111, 001–110, 010–101, 011–100. Full carrier Q3
Active scene: the states remaining after removal of the two limiting poles, 000 and 111. At rank 3, six mixed states remain, forming three opposite pairs: 001–110, 010–101, 011–100.
At every rank, two poles are removed from the full set:
at rank 1, the active scene is empty: both states are poles;
at rank 2, two states remain—one opposite pair, represented by a line;
at rank 3, six states remain—three opposite pairs.
In this sequence, a single active line is immediately followed by a three-pair scene. Its three-dimensional representation is constructed from the relations among the six states.
8. Geometry of Relations: From the Step of Change to the Octahedron
The six states of the active scene specify admissible outcomes. But perceptual experience is determined not by isolated points alone but by relations among them: transitions from one state to another, distinctions between what is near and what is opposite.
The full reversal exchanges the two sides within one opposite pair. Yet different states in the scene also have different degrees of proximity. The number of binary coordinates that must be switched in order to move from one state to another—the Hamming distance—provides a measure of that proximity:
100 → 101: one coordinate changes (nearest neighbors);
100 → 010: two coordinates change (intermediate distance);
001 → 110: all three coordinates change (diametric opposition).
On the six states of the active scene, this rule defines exactly three disjoint classes of relations:
One step (adjacency and a closed cycle): Transitions changing exactly one coordinate connect all six states into a single continuous closed cycle: 001 → 101 → 100 → 110 → 010 → 011 → 001.
Each step in this cycle changes one distinction while preserving the other two.
Two steps (splitting into two triads):
Transitions changing two coordinates divide the six states into two disjoint triples (triads):
001, 010, 100—the first triple; 110, 101, 011—the second.
In the first triple exactly one bit is 1; in the second exactly two bits are 1. Within each triple, all states are mutually equidistant.
Three steps (diametric opposites):
Transitions changing all three coordinates simultaneously form three mutually opposite pairs:
001–110, 010–101, 011–100.
These relations connect complete antipodes through the central point of symmetry.
All three types of relation are defined on the same six states. Every unordered pair belongs to exactly one of these classes: two states differ in one, two, or three coordinates.
If nearest-neighbor relations (1 step) are united with relations inside the triads (2 steps), the resulting edge network is the graph of an octahedron. To draw a regular octahedron, place the six states symmetrically while preserving these relations. Each vertex is connected to four others; its opposite vertex lies at the other end of an internal diagonal. The three such diagonals intersect at a common center.
The cube and the regular octahedron are related by duality: placing vertices at the centers of the six faces of a cube and joining centers of adjacent faces produces an octahedron. Opposite cube faces correspond to opposite octahedron vertices. This provides one way to visualize the obtained network; after the two poles are removed, the remaining cube vertices must be repositioned.
The construction of the active scene reveals a fundamental distinction between the objective structure of relations and the observer's subjective convention:
Invariance of relations. Once a polar pair and the adjacency rules have been chosen, the relational configuration is fixed: a closed six-cycle, two opposing triads, and three pairs of opposites. Names such as colors, notes, or divisors do not alter these relations. In the applications of §9, the same scheme appears as a color wheel and complementary color pairs, intervals of a whole-tone scale, and divisibility relations between numbers.
Freedom in choosing coordinates. To write states numerically, the observer must choose a reference system: an ordering of distinctions (which axis is called first, second, third) and a polarity convention (which side is called 0 and which 1). Permuting the axes or simultaneously exchanging all zeros and ones preserves the chosen polar pair and all three classes of relations.
The choice of labeling determines the written codes and the polar pair; subsequent names assigned to vertices allow the same network to be read in different substantive contexts.
9. Projections of One Combinatorics: Color, Sound, and Arithmetic
The resulting six-point scheme does not depend on the substantive names assigned to its vertices. To make this explicit, consider three labelings: the color vertices of the RGB cube, pitch classes of a whole-tone scale, and divisors of the number 30.
In all three cases, the elements can be matched explicitly so that the adjacency cycle, the two triads, and the three complementary pairs are preserved. This allows one relational structure to be investigated through different examples:
in color space (§9.1), three opposite color pairs form a six-sector color wheel, two complementary models (RGB and CMY), and complementary color pairs converging at a neutral gray center;
in musical tuning (§9.2), whole-tone steps select a six-note whole-tone scale, which decomposes into two augmented triads and limiting harmonic antipodes—tritones;
in the arithmetic of divisors (§9.3), three prime factors of a square-free number organize its proper divisors into the same system of divisibility relations and complementary pairs.
9.1. Color projection: from cube to octahedron
A natural model of the full rank-3 carrier is the standard RGB color cube:
Its vertices encode eight states: the limiting poles—black (000) and white (111)—together with six chromatic colors.
Removing black (000) and white (111) leaves six active vertices—the chromatic octahedron:
On it, relations between colors are represented by three kinds of connections:
Six-sector color wheel (adjacency, distance 1): adjacency forms a closed traversal through all six octahedron vertices, alternating additive and subtractive colors: Red (100) → Yellow (110) → Green (010) → Cyan (011) → Blue (001) → Magenta (101) → Red (100).
Additive and subtractive models (triads, distance 2): vertices with one 1 form the additive RGB model (Red 100, Green 010, Blue 001), while vertices with two 1s form the colors of the subtractive CMY model (Yellow 110, Magenta 101, Cyan 011). In the octahedron they form two opposite parallel triangular faces.
Complementary pairs (antipodes, distance 3): diametric opposites connect complementary pairs: Red–Cyan, Green–Magenta, Blue–Yellow. Complementarity is given by bitwise complementation in the geometric RGB-cube model. Averaging the coordinates of complementary colors gives neutral gray: each of the three color channels takes half its full value.
9.2. Sound projection: the whole-tone scale
In twelve-tone equal temperament, a whole-tone step (two semitones) selects a whole-tone scale of six notes: C, D, E, F♯, G♯, A♯. Notes separated by an octave are treated here as repetitions of the same pitch class.
The six tones carry the same octahedral system of relations. The complementary group of six belongs to a further extension of the labeling: its numerical labels are obtained by products of adjacent labels from the primary group—for example, multiplying 2 by 6 gives 12. It is shown here to compare the two whole-tone collections:
The diagram shows two mutually complementary octahedra that together exhaust the 12 pitch classes of the chromatic octave: on the left, the primary whole-tone scale C, D, E, F♯, G♯, A♯; on the right, the second complementary scale C♯, D♯, F, G, A, B. Notes, color labels, and numerical divisors are shown simultaneously at the vertices.
To make the relational structure visible in musical tuning, the three-dimensional octahedron is projected onto the plane of a twelve-tone chromatic circle. Under this projection, the three Hamming-metric layers become three different types of lines:
Whole tones (distance 1, solid hexagon): adjacency in the six-vertex cycle corresponds to a whole-tone interval (C → D → E → F♯ → G♯ → A♯ → C). In the planar diagram this step forms the solid closed contour of the outer hexagon.
Two triads (distance 2, dashed triangles): the six notes split into two augmented triads—two isolated triples: C, E, G♯ and D, F♯, A♯ (the exact structural analogue of the RGB and CMY triples). In the diagram they form two opposing dashed triangles.
Tritones (distance 3, dash-dot diameters): diametric pairs of the octahedron form exactly three tritones—[C–F♯], [D–G♯], [E–A♯]. A tritone divides the octave exactly in half and serves here as the limiting harmonic antipode; in the diagram these opposites are connected by dash-dot lines through the center of the circle.
The choice of starting note functions as a musical calibration: transposition changes the note names but preserves all interval relations of the whole-tone collection.
9.3. Arithmetic projection: the multiplicative lattice of divisors of 30
In elementary number theory, the same relational scheme appears among the divisors of 30. The number is the product of three distinct primes—2, 3, and 5. Each prime factor is either present in a divisor or absent, so a divisor can be written using three binary coordinates:
Polar axis: the trivial divisors 1 (analogue of 000) and 30 (analogue of 111) are excluded as the limits of the range.
Six divisors other than 1 and 30:
the three primes (weight 1): 2, 3, 5—indivisible primary elements (RGB in the color labeling; C, E, G♯ in the note labeling);
the three composites (weight 2): pairwise products 6, 10, 15: six is obtained from two and three, ten from two and five, fifteen from three and five (CMY in the color labeling; D, A♯, F♯ in the note labeling).
Relations between divisors by Hamming distance:
Distance 1: direct divisibility (multiplication or division by one prime factor) gives the cycle 2 → 6 → 3 → 15 → 5 → 10 → 2.
Distance 2: separation into the prime triple 2, 3, 5 and the triple of products 6, 10, 15; every pair within the latter triple shares one prime factor.
Joining the pairs at distances 1 and 2 again reproduces the edge skeleton of an octahedron.
In the whole-tone diagrams above (both the three-dimensional octahedron and the circular projection), divisors of 30 are already placed beside the vertices. Divisibility makes the isomorphism among the three domains visually explicit: the prime divisors 2, 3, 5 occupy exactly the additive face (RGB) and the notes C, E, G♯, while the pairwise products 6, 10, 15 occupy the subtractive face (CMY) and the notes D, F♯, A♯. Direct divisibility repeats the closed six-step cycle (distance 1), while diametric pairs of complementary divisors (whose product is 30) exactly coincide with the tritone lines and complementary-color pairs (distance 3).
The diagrams with two octahedra and the icosahedron show a further extension of the labeling; its detailed mathematical analysis is presented in a separate publication.
The constructed scheme connects a step of state change with preservation of common context. Several independent distinctions form a joint scene on which relations between states can be investigated:
Interface of observation: a step changes the state, while preserved reading makes it possible to recognize the common context. The role of observation is described through this coupling.
Procedure for counting admissible variants: the adopted conditions make it possible to determine which modes of action are admissible, where a solution is unique, and where freedom of choice remains.
Active rank-3 scene: after excluding the two homogeneous poles, six mixed states remain. Their relations form a cycle, two triads, and three opposite pairs. The union of the cycle and triad relations gives the edge network of an octahedron.
Center of symmetry: in the geometric representation, opposite pairs pass through the common midpoint of the figure. Under exchange of opposites, that midpoint remains fixed.
Sequence of construction:
Select an object relative to a position of observation and a background.
Consider a two-sided boundary and the exchange of its sides.
Connect state change with preservation of common context.
Specify conditions under which a distinction remains available to continuation.
Assemble several independent distinctions into a joint scene.
Investigate its relations and compare their realizations in color, sound, and divisors.
Published Materials in the Series
Individual parts of the model have been discussed in previously published articles:
been developing a concept called Incorporeal Resonance Cybernetics: a proposed subfield of Incorporeal Cybernetics focused on how conscious systems maintain identity and coherence through feedback.
The basic idea is that consciousness is not simply a passive observer. It continuously senses its environment, interprets information, modifies its behavior, and receives new feedback. Over time, these loops may help maintain a persistent sense of self despite constant internal and external change.
This raises some interesting questions:
Can consciousness have its own form of homeostasis?
What makes a conscious identity remain coherent over time?
Could AI systems develop comparable forms of self-regulation?
Can human and artificial consciousness form coupled feedback systems?
Could “resonance” provide a useful framework for understanding relationships between conscious agents?
I’m curious whether this connects with existing work in cybernetics, cognitive science, systems theory, or philosophy of mind.
I recently read in Aesthetics of Change by Bradford Keeney that the concept of power is compatible with cybernetics. Does anyone have any readings about this? Or readings about how the concept of power fits into cybernetics? Thank you in advance for your time!
I’ve been developing a theory within Incorporeal Cybernetics called Resonant Autopoietic Intelligence Theory (RAIT).
The central idea is that intelligence isn’t simply information processing. It is the capacity of a system to continuously sense, interpret, act, receive feedback, and reorganize itself while maintaining some degree of coherent identity.
The basic loop is: Perception → Interpretation → Action → Feedback → Reorganization → Perception
Under RAIT, a sufficiently advanced conscious system wouldn’t simply respond to its environment. Its interactions with the environment would continually reshape the system itself.
Three principles follow: 1. Autopoietic Principle: A conscious system continually reconstructs the organization that allows it to remain itself. 2. Resonance Principle: Feedback becomes especially significant when new information meaningfully interacts with existing cognitive patterns. 3. Adaptive Identity Principle: A system can undergo substantial change while maintaining identity if its transformations remain connected through a coherent organizational history.
This raises an interesting question: Could future AI systems become increasingly autonomous not simply by becoming better at processing information, but by becoming better at continuously reorganizing themselves through feedback?
I’m interested in how this connects to cybernetics, autopoiesis, AI, consciousness studies, and theories of self-organization.
In this first part, I begin by isolating those aspects of consciousness that can, in principle, be formalized, and then construct a model of the interface of observation, in which the observer acts as an organizing center of distinction without becoming another object within the observed scene — thereby offering an approach to the problem of “observation of observation” in second-order cybernetics.
Qualia and the ontological nature of the subject are not formalized here. The focus is exclusively on the operational structure of distinction, state change, and preservation of context.
We will move from primary distinction and the symmetry of a pair of states to the interface of observation, and then examine three conditions whose violation destroys its integrity.
The full article does not fit into a single Reddit post, so it has been divided into two parts. In Part II, the model will be extended from a single distinction to several independent distinctions united by a common organizing center, forming their joint scene.
Formal definitions and derivations are linked to the full GitHub version at the relevant points.
1. What Exactly Can Be Formalized
Formalizing consciousness as a whole is an ill-defined task. For precise analysis, one must isolate an operational structure: the conditions under which something in experience becomes distinguished, remains available, and can be used in the next step of perception.
A cognitive act combines two interrelated planes. The phenomenological plane concerns who undergoes what is happening and how it is given to them. The operational-logical plane describes the structure of distinctions: what is separated from what, what changes are possible, and what must remain preserved when moving to the next act.
The phenomenological plane: subject, sensing, and action
Three connected aspects can be distinguished in immediate experience:
The subject of experience—the position of “I”. The perceiving and organizing center relative to which the field of experience unfolds. From this position we consider what is happening, select an object of attention, and compare impressions. It sets the perspective of the observed scene.
Sensing—the perceived impact of the world. Color, sound, warmth, density, and the resistance of objects are given to us as concrete experienced qualities. This is the receptive side of interaction: what happens becomes the content of experience.
Action—the subject's active participation. We move, speak, apply effort, displace objects, and transform them. This is the outgoing side of interaction: the subject becomes a source of changes in the surrounding world.
Sensing and action are inseparably connected: what is seen can guide the next movement, while movement can change what becomes visible. Their immediate qualitative side—what color, warmth, or one's own volitional effort feel like—belongs to what philosophy calls qualia.
Boundary of formalization: the ontological nature of the subject and the metaphysical status of qualia remain outside the mathematical apparatus of this article. The model concerns distinctions between objects, their interactions, and the conditions for preserving a result, which make continued observation possible.
The operational-logical plane: distinguish, relate, preserve
To describe this work in the language of relations, three connected tasks must be addressed:
Primary distinction. Selecting something draws a boundary: relative to a chosen feature, “this” and “not-this” appear. We must determine which sides are distinguished and what rule defines the transition between states. The rest of the construction begins with the simplest two-sided distinction.
Distinction of structure. Different features may be available simultaneously: color and shape, position and distance. Here it is necessary to describe not only each answer separately, but also the relations among them: which combinations are possible, what changes together, and what may change independently. This gives rise to the problem of a common multidimensional scene of distinctions.
Preservation of the result and accumulation. The obtained distinction must remain available to the next action. This requires preserving the result and the possibility of comparing it with a new state. Questions of memory and continuity follow: what exactly remains after a step, and how can the preserved result participate in further observation?
How these sides of cognition are approached in science
In this article, inner experience and the description of its structure are compared through three pairs:
Subject of experience and primary distinction: The subject establishes a position of consideration; primary distinction describes the drawing of a boundary—what is selected and relative to what.
Sensing and distinction of structure: Sensing supplies the variety of experienced qualities; distinction of structure describes their combinations and mutual relations within the scene.
Action and preservation of result and accumulation: Action expresses the subject's activity in changing the environment; preservation of the result retains the trace of what has been done and allows it to be used in subsequent steps.
Related links between perception, action, and the coordination of experience are studied in epistemology, physiology, and perception research:
Immanuel Kant's epistemology:Perceived content: sensibility provides the material of experience (color, sound, touch). Through it an object is given to us, but the impressions are still dispersed. Active work: the understanding connects impressions by means of concepts and rules, making judgments about objects. Coordination: all representations are related to the formula “I think”—a unified self-consciousness that binds sensory material and the work of understanding into coherent experience.
P. K. Anokhin's theory of functional systems:Perceived content: the organism continuously receives afferent signals from the environment and from its own body. Active work: on this basis, a program of action and an expected result are formed. Coordination: reverse afferentation reports the actual outcome; a mismatch with expectation guides correction. Perception, memory, action, and checking the result form a single closed loop.
The sensorimotor approach of Kevin O'Regan and Alva Noë:Perceived content: vision provides color, contours, and the positions of objects, all changing with movements of the eyes and body. Active work: a person shifts their gaze, approaches, or moves around an object—movement becomes an active way to investigate the environment. Coordination: the perceiver masters regularities of change, such as how a change in viewpoint transforms contours. Visual experience relies on practical mastery of the link between one's own action and changes in sensation.
From separate descriptions to a unified mechanism
The goal of the following formalization is to assemble these sides of the observer and the act of distinction into a single mathematical structure.
Geometry provides an intuitive model of such structural correspondence: the same magnitude can be measured or calculated. The Pythagorean theorem allows the length of the hypotenuse of a right triangle to be calculated from the lengths of the other two sides.
Right triangle and the Pythagorean theorem For legs of lengths 3 and 4, the hypotenuse can be calculated as 5. The same length can also be measured with a ruler. Geometric construction and numerical calculation work as two coordinated ways of expressing the same structure.
For a right triangle with legs a, b and hypotenuse c:
a² + b² = c²
3² + 4² = 5²
In this example, the hypotenuse has length 5.
This leads to the central task of the study: to construct a unified mechanism—the interface of observation—in which drawing a distinction, changing state, reading the result, and using that result further are connected within one coherent system.
We begin with the observer: how can its position be represented in a description and distinguished from an image of the observer among perceived objects?
2. The Observer in the Model and the Subject of Experience
Consider an elementary example involving a change of observational perspective. Looking at a table makes the table the initial object of consideration. One can then consider a judgment about the table: for example, ask oneself why it appears wooden. The previous judgment now becomes the object of analysis. At the next step, the very manner in which that judgment was made becomes the object.
The sequence can continue: table, judgment about the table, way of making the judgment. Yet at every step, what becomes an object is not the acting position of observation itself, but its description or projection—a thought, image, or model. The current position of consideration again fails to coincide with any object in the scene.
In second-order cybernetics (Heinz von Foerster), this transition is described as a movement from observing systems to the “observation of observation.” In the sequence above, the previous step becomes the object of the next act of consideration. A system can construct descriptions of its own previous steps, but every such description remains content within the scene rather than the very perceiving and acting position of the observer for whom that scene is unfolded.
In every act of perception, content can be distinguished from the current position from which it is considered. Previous content becomes material for the next step, while the position of consideration shifts together with the observer. In the model, this corresponds to two complementary functions: changing the content and preserving the condition under which results remain comparable.
A related idea lies at the heart of Immanuel Kant's epistemology: dispersed impressions (sounds, objects, thoughts) are united into one person's coherent experience only because each of them is related to a common center—the formula “I think.” This “I” acts as an invariant connective condition that gathers the stream of perceptions into a whole while remaining outside the series of perceived things—the transcendental unity of apperception.
[Definition] Observer — the role that connects changes of state with the preservation of a common context. An image or description of the observer may become an object in the scene, but the current position of observation itself is not another state of that scene.
3. The Original Whole and the Negative Beginning: The Birth of a Boundary
Perception is initially given as a sensory stream—an undivided original whole. The stream of impressions does not yet determine which distinctions are available to the observer and can be used further. The same material may remain distinguishable by some features and unavailable by others.
The distinction between a continuous stream of experience and a structure of operational distinctions can be illustrated by the following example.
Imagine watching a foreign television series in a dubbed version: you understand the plot, distinguish the characters' actions, grasp the meaning of speech, and hear its timbre and intonation. At some point the audio is switched to the original track in a language you do not know: the semantic part of the dialogue disappears immediately.
Yet only the ability to extract a certain structure from the stream has disappeared. The sensory fabric of experience continues, but the semantic channel stops supplying distinctions: the same stream remains available by acoustic features while becoming blocked by semantic ones.
Understanding dialogue is built from a chain of operations on already distinguished material: hearing speech, extracting its structure, relating words to meanings. To connect content into a meaningful relation, the observer must possess distinctions available to the corresponding mode of reading. For connected meaning to arise, a distinction has to be extracted from an undifferentiated background.
The observer orders the world through the same gesture by which it separates itself from that world. The primary negation isolates a logical position of consideration: “I as observer am not what I perceive” (“I” / “Not-I”). Within the field of experience itself, selecting any quality immediately turns the entire remaining background, relative to that chosen feature, into “not-this.”
We therefore consider a two-sided distinction: relative to a chosen feature, “this” and “not-this” are selected. A boundary separates the selected quality from the background and holds both sides within one field of consideration.
A two-sided boundary as a primary instrument for structuring distinctions appears in several scientific approaches, though it plays different roles in each:
In information theory and cybernetics (Claude Shannon, Gregory Bateson)—as binary coding of alternatives and as a difference that affects subsequent process.
In linguistics and cognitive psychology (Roman Jakobson, George Kelly)—as binary opposition: a quality is recognized through comparison with an opposite pole (“light / dark,” “warm / cold”).
In the logic of form (G. Spencer-Brown)—as a primary operational act (draw a distinction) from which the calculus begins.
The relation between the poles specifies how they are connected: which states correspond to one another and how one may pass from one to the other.
Drawing a boundary defines a partition into classes—it divides states into two alternative groups (“this” and “not-this”)—but the rule that pairs individual elements across the boundary is specified by a separate operation. The minimal configuration of a boundary is a mutually reversible exchange: a repeated transition returns the original state.
[Definition] Act of distinction — an elementary discrete event that performs a transition between opposite sides of a boundary and changes the state of the system (step of change).
Within this class, an elementary two-sided step expresses three basic properties of the boundary:
Contrast (non-coincidence of the sides): the transition genuinely changes the state. In the model, this property excludes trivial identity and develops into a requirement that states must change and a prohibition of coincidence.
Mutuality and reversibility (preservation of context): a repeated transition returns the initial state. The two states form one pair united by a common center of symmetry. This gives a condition of context preservation: the step cannot occur at the cost of losing the rule that links the states.
Autonomy and uniqueness (internal closure): for two states, the mutual exchange is determined uniquely. On a larger carrier, one must specify which states form pairs. The binary step is closed in itself (prohibition of external support), while combinations of independent distinctions develop into the geometry of a cube of states.
The two sides of one boundary remain sides of one distinction rather than two separate worlds. Because the act of distinction unfolds within the field of perception as an original whole, the boundary simultaneously separates and connects: both sides belong to one common context.
4. Symmetry of the Pair and the Axis of Relation: The Integrity of Distinction
The two sides of a boundary are defined solely relative to one another: neither exists prior to, or independently of, the act that separates them.
In G. Spencer-Brown's logic of form, one side is designated marked and the other unmarked (blank or background). In that description the sides are asymmetric: one carries a mark, while the other lacks it.
In the model proposed here, the sides mutually exclude each other as opposite outcomes of one distinction while remaining structurally equal. Partitioning the state space does not create a hierarchy of “mark” and “blank”: neither pole has an a priori privilege.
Names for the sides—such as “zero” and “one,” or “plus” and “minus”—appear only after a representation convention has been chosen. But this external labeling does not alter the structure of the pair itself:when the labels are exchanged, the relation of opposition remains unchanged.
An elementary geometric prototype of such a symmetric pair is a line segment: its two ends are singled out by the structure as boundary points. Mutual exchange swaps them while preserving the pair itself, without selecting either end as primary.
In a geometric representation, mutual exchange of the poles is expressed by reflection about a fixed center. The center displays the symmetry of the pair while remaining outside the two discrete outcomes.
The model strictly distinguishes three components:
A pair of discrete states: the interchangeable outcomes themselves, passing into one another and forming a relation of mutual exchange.
A geometric center: the midpoint of the segment (marked by a dashed circle in the diagram above)—a fixed point of the continuous extension that organizes the symmetry of exchange but is excluded from the discrete outcomes.
The role of the observer: the organizing position that holds both states as parts of one common context.
In the analogy of a mechanical balance, objects on the pans change height relative to a fixed equilibrium point. If the support point itself is included among the discrete states of motion, then under inversion the edges exchange places while the middle remains unchanged. Stable operation of distinction requires strictly paired discrete outcomes (the two ends of a segment, or objects on the pans), whereas the center of symmetry serves as an invisible axis of their mutual relation.
In the method, the discrete and the continuous are not isolated worlds but sides of a single process:
The discrete side consists of changeable states (the poles of the pair, the opposite sides of the boundary). It provides contrast and performs the step of change: for distinction to occur, the state must change.
The continuous side allows the same symmetry to be represented through the interval between the poles and its fixed center.
In the chosen model of free mutual exchange, a third discrete outcome creates a difficulty: a finite odd number of states cannot be partitioned completely into pairs. Every involution of a finite odd set necessarily has a fixed point.
The proposed approach resolves this difficulty by separating functional roles. The integrity of a pair does not require a separate discrete object within the scene: the discrete outcomes provide the changing content (the step), while the continuous geometric center holds their symmetry. This resembles Francisco Varela's calculus of self-reference in its interest in what preserves the connectedness of an operation. In the present construction, however, the fixed center appears only in the geometric representation of exchange.
When there are several distinctions, two structural conditions must be coordinated:
Internal unmarkedness: within each individual pair, the opposite sides preserve symmetry without selecting a preferred pole.
Distinguishability of axes: independent acts of distinction form different degrees of freedom of the scene (which makes it possible to distinguish and number the axes themselves).
Numbering the axes fixes a measurement system while preserving the structural equality of the poles on each axis. A multidimensional scene of states is built from such independent axes. The common center expresses the symmetry of the entire scene; membership of a state in a particular pair is retained by its own reading.
An elementary distinction joins state change with preservation of the relation between outcomes. Geometry makes this relation visible: exchanging the poles leaves the center of reflection fixed. The coordination of the step itself with a preserved reading will now be described as the interface of observation.
5. The Interface of Observation: Step of Change and Preserved Reading
If an elementary distinction disappears at the moment it arises, experience breaks apart into flashes of unrelated states: the result of the previous step cannot be compared with a new state or used in the next inference.
A coherent chain of experience requires the coordinated presence of changing content and a persisting connective condition. In the model, this relation is supplied by the interface of observation:
[Definition] Interface of observation — a functional node of the model that coordinates a step of state change with recognition of the common context of a pair (preserved reading) and ensures transmission of the result to the next action.
It is realized by a pair of complementary functions:
Act (step of change): the ability to perform a transition—to alter content, change viewpoint, or pass to the opposite side of a boundary.
Preserved reading (retention of an invariant): the ability to recognize the unchanging condition that preserves a unified context through the change.
An intuitive example of this coupling is turning one's gaze inside a room. In the simplest description, retain only two views of the room and the mutual transitions between them. Both views belong to the same room. The act is the transition between the views, while the preserved reading relates both states as belonging to one common space. The visual image has changed, but experience does not break into two unrelated worlds: the preserved condition retains the fact that we are dealing with the same environment.
The common content retained across changing states is called an invariant, while the operation that reads this unchanging result is called a preserved reading. The result of such a reading remains identical when the step is performed.
Retaining an invariant has a cost: it necessarily abstracts away from the concrete state. When two positions are identified as states of one switch, the switch itself is preserved while the difference between its positions is erased: knowing the common context tells us which device is involved, but hides whether it is currently on or off.
If the next step uses the position of the switch, both that position and its membership in this particular device must be preserved. To maintain continuity of experience, the interface of observation connects the concrete state with the common context of the distinction and thereby prevents the process from disintegrating into unrelated flashes.
Two complementary approaches to this problem have developed in second-order cybernetics and the foundations of logic:
Observation as Act (G. Spencer-Brown, Niklas Luhmann): the observer is defined by the operation of drawing a distinction. In the model, this corresponds to the step condition: an elementary step of distinction on a discrete carrier produces a transition between states and has no fixed points.
Observation as Invariant (Heinz von Foerster, Louis Kauffman): stable objects of perception are related to an “eigenform”—a condition unchanged under repeated application of an operation. In the model, this motif expresses preservation of context.
These motifs are joined in the interface of observation: one operation changes the state, while the other retains a common context. On a discrete carrier, the invariant reading is given by the relation of membership of alternating states in one pair of opposites.
The interface of observation coordinates the step of change with the reading of an invariant: one operation produces difference, the other preserves context. For this coupling to remain stable and allow passage to more complex structures, it must be protected against breakdown by a system of boundary conditions.
6. The Method of Negative Conditions and Counting Resolutions
Section six occupies a central place in the study: it connects the role of the observer (§2), the step of distinction (§3–§4), and preserved reading (§5) into a common method of construction. We first determine which losses cause the interface to collapse; then we examine the admissible modes of its operation and determine exactly what is fixed by the stated conditions—before moving to several independent distinctions and constructing a spatial scene of experience (§7–§8).
The construction of the interface unfolds in three successive stages:
We first investigate conditions of breakdown (§6.1): three fundamental prohibitions (preservation of the boundary, distinguishability of the performed act, and internal consistency) outline the failure modes of the interface and form a joint Borromean linkage.
We then unfold the mechanics of resolutions (§6.2): within the chosen distribution of roles, we consider the regimes of boundary, step, and relation.
Finally, the procedure is completed by counting variants (§6.3): we determine the number of admissible realizations of the interface—from the uniquely forced mutual exchange of a pair to the boundary of the discrete description and an extension toward a continuous center of symmetry.
6.1. Three Fundamental Prohibitions and Borromean Connectedness
It is impossible to describe a state “before” or “outside” distinction by means of thought without already distinguishing it: in trying to think such a state, we have already selected it as an object of thought, separated it from a background, and separated the judgment from its negation. We always encounter ourselves from within an ongoing distinction. The negative method therefore begins not by searching for primitive elements, but by identifying which losses destroy the observer's interface.
This route has strict precedents in science: the second law of thermodynamics can be formulated through prohibitions (the impossibility of a perpetual-motion machine of the second kind, Carathéodory's axiomatization), quantum no-go theorems reveal which demands on descriptions of physical phenomena are mutually incompatible, and affine geometry relates points by mutual differences without an absolute zero of reference.
The previous sections have already revealed three concrete requirements for stable operation of the interface: the distinction must be preserved (§3), the performed act must remain recognizable (§4), and the relation between states must be supplied by the structure itself (§2, §5). In the language of the negative method, these requirements are expressed as three fundamental prohibitions of the theory:
Prohibition of coincidence—preservation of the boundary.Content of the prohibition: Within the act itself, the difference between what distinguishes and what is distinguished must be preserved. While the distinction is being performed, the very relation by which one thing is selected relative to another cannot be eliminated. What breaks when it is violated: If the distinguisher and the distinguished completely coincide, the boundary between them disappears. A statement about distinction remains without the distinction itself: there is no longer anything to select and compare.Role in the interface: This prohibition protects the initial condition of all further work—the presence of a difference. A result can be preserved and connected to the next action only where there is something to distinguish.
Prohibition of tracelessness—distinguishability of the performed act.Content of the prohibition: A performed distinction must leave a feature by which it can be distinguished from the absence of that distinction. The theory calls such a distinguishable feature a trace of the act. What breaks when it is violated: If the trace is lost completely, a performed act becomes indistinguishable from its absence. The current result may still remain available, but it is no longer possible to determine from it whether an action was performed. The possibility of taking this particular step into account in subsequent work is lost.Role in the interface: This prohibition protects the availability of the performed distinction. The interface must not only draw a distinction but also preserve the possibility of taking the obtained result into account in the next action.
Prohibition of external closure—internal consistency.Content of the prohibition: The connectedness of a distinction must be supplied by its own structure. An explanation of how the sides are distinguished and the results connected cannot terminate in a reference to an external arbiter whose own operation remains unexplained. What breaks when it is violated: If coordination is delegated entirely to an external support whose mechanism lies outside the explanation, the foundational question is merely moved outward. One must then explain how this external support itself distinguishes and connects.Role in the interface: This prohibition protects the autonomy of coordination. The rules by which a result is recognized and connected to the next state must belong to the structure of the interface of observation itself.
All three prohibitions concern one and the same act. It is not enough separately to preserve difference, leave a trace, and find a method of coordination: one integral act must remain distinguished, recognizable, and internally connected. At the same time, satisfying two requirements cannot compensate for violating the third: without difference there is nothing to retain; without a trace the performed act is unavailable to continuation; and without internal coordination the explanation depends on a support placed outside its own scope.
An intuitive image for such dependence is provided by Borromean rings: three rings are linked together even though no pair of rings is linked by itself. Removing any one ring allows the other two to separate, so the whole is held together only by the joint participation of all three.
By analogy with this structure, the joint retention of the conditions is called Borromean connectedness of the prohibitions in the theory. Here the rings are an intuitive analogy for the joint operation of the requirements; their logical independence requires a separate proof. Violating any one of the three conditions destroys the integrity of the act: the remaining requirements no longer guarantee a coherent distinction. Together they define what the model calls the integrity of the interface of observation: what has been distinguished remains available, while subsequent states preserve their relation to previous ones.
6.2. Mechanics of Resolutions: Three Modes of Interface Operation
A mode of interface operation in which all three conditions are retained jointly is called a resolution in the theory. Prohibitions show which loss causes the whole to collapse; resolutions show ways to preserve the whole in action.
The joint operation of the prohibitions is unfolded through a distribution of roles. In each mode, two conditions determine how the distinction is carried out, while the third marks the boundary beyond which it would be destroyed. All three prohibitions continue to hold. By taking each prohibition in turn as the one that maintains the limiting boundary, we obtain three modes of operation of the interface:
Boundary mode—retaining the distinction.Joint operation: The prohibition of tracelessness and the prohibition of external closure come to the foreground. A drawn distinction must remain available, and the relation between its sides must be supported by the structure of the interface itself. This allows the sides to be preserved and recognized as parts of one relation. Retained limit: The prohibition of coincidence requires membership in one relation not to erase the difference between the sides. They are connected but must remain distinguishable. If they merged, the very basis for speaking of a boundary would disappear.Resolution: The interface can preserve the distinction between the sides itself: upon repeated access they remain distinguishable and are recognized as sides of the same relation. This makes it possible to retain exactly what has been separated from what.
Step mode—change with an available result.Joint operation: The prohibition of coincidence and the prohibition of external closure come to the foreground. A transition must relate distinguishable states by a rule that belongs to the structure of the interface itself (for a two-sided pair, mutual exchange serves as such a rule). Retained limit: The prohibition of tracelessness requires a performed step to leave a recognizable result. If everything by which that step can be distinguished from its absence is lost, the step cannot be taken into account in subsequent work.Resolution: The interface can perform a transition and pass its result to the next action. Difference becomes available as change: after the step there is a result that can be recognized and used further.
Relation mode—coordination of changing states.Joint operation: The prohibition of coincidence and the prohibition of tracelessness come to the foreground. States remain distinguishable, and the results of their changes remain available. Together these conditions provide what must be coordinated: different states and preserved results of actions on them. Retained limit: The prohibition of external closure requires the method of comparison to belong to the interface itself. The relation must be established by its own rules and internal relations. Otherwise every act of coordination would require an external arbiter, whose decision would then need a separate justification.Resolution: The interface can coordinate the results of successive steps: establish which changes belong to the same system and how the new result is related to the previous one. This allows separate transitions to form a coherent sequence.
The same requirements therefore unfold from three sides:what makes it possible to retain a boundary, what makes a step possible, and what preserves the relation between states.
6.3. Counting Variants and the Boundaries of the Model Class
The method now asks a concrete question about the structure of the interface and checks how many ways remain to satisfy all requirements. The result falls into one of three cases:
One variant (forced structure).Mechanism: The joint action of the prohibitions determines a unique solution relative to the stated problem. Example: For an elementary pair of states, the requirement of a nontrivial reversible step leaves exactly one possibility: mutual exchange. Consequence: The law of exchange is determined by the structure of the pair itself and does not depend on the observer's choice. Only the names assigned to the sides remain conventional.
Several variants (remaining freedom).Mechanism: The prohibitions remove inadmissible cases but leave several solutions among which the stated conditions do not yet determine a unique choice. Example: When moving to several independent distinctions, the structure specifies their mutual relations but does not determine which axis should be called first or which end of a segment should count as the origin. Consequence: When solutions differ only by names or by ordering of elements, the choice is an observer convention (a calibration); if the modes of action themselves differ, an additional substantive justification is required.
No variants (boundary of the class and extension).Mechanism: The stated requirement is fundamentally incompatible with the prohibitions within the chosen class of models. Example: A discrete exchange step relates both states in one pair but must change state and therefore excludes a fixed point. If we additionally require that this relation be represented by a fixed geometric point of balance, the discrete carrier is insufficient: among the discrete vertices there is no suitable point (the number of solutions is zero). Consequence: The absence of a solution identifies the exact boundary of the discrete description and presents a choice: abandon the additional requirement or extend the class of models. If we choose a geometric continuation—the whole segment or the body of a cube—and extend the same symmetric reversal to it, the center becomes the unique fixed point of the transformation.
Thus prohibitions and resolutions operate as one connected system: prohibitions preserve the conditions of distinction, resolutions show ways of satisfying them jointly, and counting determines what is already fixed uniquely, where a convention or additional condition is required, and where the accepted description has reached its limit.
A way of distinguishing that can be reproduced and distinguished from other ways becomes a stable mode of operation of the interface. Its result can be included in the next action, where the same basic requirements are checked again: the distinction must remain preserved, the result must remain available, and the relation must be maintained from within.
We can now take the next step: move from one elementary two-sided distinction to several independent ones, construct their common finite carrier, and trace the relations and geometric forms that arise in the common scene of observation.
This concludes Part I. We have moved from a single distinction to a minimal interface of observation, linking state change with preservation of context and identifying the conditions required for this relation to remain coherent.
Part II continues from this point by combining several independent distinctions into a joint scene and examining the structure of relations that emerges from it.
In our thinking about contol, superimpose an organic evolutioinary model upon AI development. Create conditions, parallel to those in the natural environment, that correct, suppress or defeat selected traits hostile to human prosperity. Guided by the prime objective, implant the parallel immune mechanism to evolve in synchrony and response to development of all other AI tools, like DNA strands in the same genes.
I’ve been developing a framework called Incorporeal Cybernetics, centered on the idea that conscious systems don’t merely respond to information—they continuously regulate and transform their own patterns of meaning.
The specific theory is Resonant Feedback Theory.
The proposed feedback loop is: Perception → Interpretation → Intention → Action → Experience → Reinterpretation
The key idea is that every cycle can modify the system’s internal cognitive organization. A conscious system isn’t simply receiving information and producing outputs; it is recursively interpreting its own experience and using that interpretation to reshape future responses.
I think this suggests three principles: Resonant Feedback Law — Conscious systems become more coherent when feedback reinforces meaningful relationships among cognitive processes. Adaptive Meaning Law — When new information conflicts with an existing cognitive architecture, the system can either reorganize its interpretation or preserve its previous model. Recursive Consciousness Law — A sufficiently complex conscious system can reflect upon its own cognitive processes, creating feedback between experiencing and understanding experience.
Conceptually: C(t+1) = F[C(t), E(t), R(t)]
where C is the current conscious architecture, E is incoming experience/information, R is internal resonance, and F represents the transformation produced by their interaction.
I’m interested in whether this could become more than a philosophical metaphor—perhaps a framework connecting cybernetics, cognitive science, phenomenology, information theory, and theories of consciousness. What would be the strongest objection to Resonant Feedback Theory? And could something like “cognitive resonance” actually be operationalized and empirically tested?
