The Human Instability Principle

An Essay by Luc Lelièvre

The Closure series has argued that institutions can continue functioning long after they lose the capacity for self-correction. Fragility of Closure located the weakness inside the institution: categories and routines become resistant to revision, and the very sophistication that makes a system look strong is often what prevents it from learning. The Human Instability Principle takes the argument to the other side of the relationship. The weakness is also in what administration tries to administer. Human beings are not fixed objects whose relevant characteristics can be recorded, stored, and acted upon. They respond to the systems that classify them, and their responses become part of the environment those systems must then try to interpret.

Luc Lelièvre draws on the Austrian tradition, Mises, Hayek, and Kirzner, to make the case that the knowledge required to control human behavior is dispersed, continually changing, and partly created by people responding to the control itself. The essay sets this against the current ambition of total administration: digital identification, predictive analytics, biometric surveillance, risk scoring, AI-driven classification. The capability is real. What the capability cannot deliver is a stable object. The more comprehensive the control system becomes, the more it alters the conditions on which its own predictions depend.

The essay engages directly with the technocratic future Derrick Broze and others have been describing. Lelièvre’s argument is that the people being administered will not stay still long enough to make the system coherent. The Vietnam War illustrates the loop. American intervention changed the environment, Vietnamese actors adapted, and the adaptations undermined the assumptions on which the next intervention was built. Daniel Ellsberg’s work on the Pentagon Papers exposed the pattern from the inside: successive administrations knew their models were failing and continued to escalate anyway. The “Prison Planet” is not unstable because technology is limited. It is unstable because the human beings inside it remain human.

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The Human Instability Principle

Why Total Control Cannot Solve the Knowledge Problem

An Essay by Luc Lelièvre

The dream of total control predates modern technology. Governments have always sought ways to make human behavior more predictable: through laws, classifications, registration, surveillance, administrative routines, and systems of authority. What has changed is not the ambition itself but the scale of the tools available to pursue it. Digital identification, artificial intelligence, biometric surveillance, predictive analytics, and increasingly sophisticated data systems now enable institutions to observe, classify, and process human behavior on a scale earlier governments could scarcely have imagined.

This technological expansion suggests a familiar conclusion. Perhaps the remaining uncertainties about human behavior are fundamentally informational. Perhaps sufficiently powerful computers, paired with sufficiently comprehensive data, will eventually enable institutions to anticipate human actions with enough precision to make society effectively manageable.

That conclusion rests on a misunderstanding of the issue.

The obstacle to total control is not merely technological. It is epistemic because the knowledge required to control human behavior is dispersed and constantly changing. But the problem is also anthropological. Human beings are not fixed objects whose relevant characteristics can be recorded and stored. They learn, adapt, improvise, cooperate, resist, reinterpret, and discover.

They respond to the institutions that seek to regulate them, and their responses become part of the environment those institutions must address.

There is therefore a fundamental instability inherent in any attempt to administer human beings comprehensively.

This is what I call the Human Instability Principle.

Human beings cannot be rendered fully predictable by the systems designed to administer them because the knowledge relevant to their behavior is dispersed, continually changing, partly created by their responses to institutional action, and rooted in forms of human agency that administration cannot fully eliminate.

The principle does not imply that governments cannot exercise considerable control. They can.

The argument is narrower: the broader the scope of attempted control, the more the system alters the conditions on which its predictions depend.

The Fantasy of a Knowable Population

Every system of comprehensive administration requires a specific conception of the population it governs. People must become sufficiently stable objects of classification to be counted, categorized, measured, compared, monitored, and acted upon. Individuals become cases, profiles, risk categories, scores, records, demographic groups, or statistical observations.

There is nothing inherently wrong with this process. Complex societies could not function without categories. Governments need classifications to administer programs. Universities need procedures to evaluate students. Hospitals need diagnostic categories. Corporations need organizational structures. Regulatory institutions need standards and indicators.

The problem arises when the representation becomes more stable than the reality it was meant to represent.

An institution creates a category to make reality manageable. Once established, however, departments, budgets, procedures, professional routines, reporting requirements, and performance indicators begin to organize around that category. Information that fits the classification moves relatively easily through the institution, while information that does not fit must be translated, reclassified, postponed, referred elsewhere, or treated as an exception.

The category consequently ceases to be merely a representation of reality and becomes part of institutional reality.

This creates a problem that grows more serious as administration becomes more elaborate. The institution can change how it represents the individual without necessarily changing its understanding of the individual. Administratively, a person may be reduced to a file, a number, a risk profile, a consumer category, a health record, an employee identifier, or a behavioral prediction.

Yet none of these representations exhausts the person.

The individual continues to interpret circumstances, make judgments, revise expectations, and act on knowledge that may never be reflected in the institutional representation.

The institution may therefore possess information about a person without the knowledge required to understand how that person will respond to classification, monitoring, or control.

This is where the problem of administration becomes inseparable from that of human agency.

The Austrian Knowledge Problem

The Austrian tradition offers an important starting point for understanding this limitation.

Ludwig von Mises demonstrated that economic calculation cannot be replaced by the mere accumulation of technical information. An administrator might possess extensive knowledge of available resources, technologies, labor, and production methods yet still lack the means to determine which allocation of those resources is economically rational. The problem is not simply a lack of information. Rather, economic calculation requires a mechanism for comparing alternative uses of scarce resources.

Friedrich Hayek extended this problem beyond economic calculation. In his famous 1945 essay “The Use of Knowledge in Society,” he argued that the knowledge required for social coordination is dispersed among millions of individuals and is often local, temporary, contextual, and tacit. It is not simply waiting somewhere to be collected by a sufficiently powerful authority.

This distinction matters because the knowledge problem is not solved merely by increasing the amount of information available to the center. The authority must still determine which information matters, when it matters, how it should be interpreted, and what institutional response it should prompt.

Israel Kirzner adds another dimension to this argument. Knowledge is not simply dispersed; some of it remains undiscovered. Entrepreneurial alertness enables people to notice opportunities, errors, and possibilities that no central authority could have specified in advance. Kirzner’s account of competition therefore emphasizes a process of discovery rather than a static distribution of information.

Taken together, these insights indicate a broader administrative problem.

A system attempting to control human behavior does not confront a population whose relevant characteristics are already known. It confronts people who possess knowledge, discover it, and generate new knowledge through their actions.

More importantly, those people are responding to the system.

The institution is therefore not observing an independent, stationary object. It is intervening in the very process it aims to predict.

Human Beings Are Not Administrative Variables

Human beings do not merely provide information to institutions. They also respond to those institutions.

A new regulation changes incentives. A new classification changes how individuals understand their circumstances. A surveillance system can alter behavior simply because people know they are being observed. An eligibility rule changes the strategies people use to qualify. A new penalty changes the perceived cost of specific actions.

The object of administration therefore changes as it is administered: the intervention alters incentives and circumstances, people respond, and those responses become part of the environment the institution must later interpret.

The central point is not that human beings are irrational, chaotic, or incapable of coordination. Rather, they are adaptive agents who interpret circumstances, revise expectations, abandon ineffective strategies, explore alternatives, cooperate, and sometimes resist rules they deem illegitimate or intolerable.

None of this is an exceptional failure of human rationality. It is part of ordinary human behavior.

Indeed, the very capacity that makes human beings difficult to administer is also what makes social coordination possible. People learn from their environment precisely because they are not passive objects within it.

An institution attempting to predict human behavior cannot remain external to the process it seeks to predict. Its intervention alters the conditions under which subsequent behavior occurs.

The observer becomes part of the system under observation.

The Anthropological Limit

However, there is a further problem that cannot be reduced to Hayek’s theory of knowledge distribution.

Human beings do not merely adapt strategically. They also respond to the meaning of the conditions in which they live.

They care about being treated as persons rather than as objects. They value autonomy, recognition, dignity, belonging, and the ability to give meaning to their actions. They may accept considerable restrictions when those restrictions are perceived as legitimate, intelligible, and compatible with their self-understanding. They may respond very differently when the same restrictions are perceived as arbitrary, degrading, or totalizing.

This does not mean that every individual will respond the same way. It means that human behavior cannot be reduced indefinitely to the variables an administrative system measures.

A database can record a person as a citizen, consumer, employee, patient, student, member of a risk category, or as a biometric identity. It can accumulate an extraordinary amount of information about that person. Yet the administrative representation remains just that.

It does not become the person.

The distinction is especially important when institutions try to compress dimensions of human existence that are difficult to quantify. Meaning cannot be reduced to a score. Dignity cannot be fully captured by an indicator. Recognition cannot be guaranteed by a database entry. Autonomy cannot be reduced to the number of options technically available to an individual.

When these dimensions are systematically ignored, the resulting tensions do not necessarily dissipate.

They may accumulate.

The institution may then interpret the resulting behavior as non-compliance, deviance, irrationality, misinformation, extremism, or resistance. Sometimes such interpretations are justified, but at other times what appears to be instability in the population is partly a consequence of the system’s own attempt to stabilize it.

A system can therefore misinterpret the consequences of its intervention.

This is one of the most significant limitations of comprehensive administration.

This argument also develops a distinction introduced in Fragility of Closure. There, the weakness lay within the institution: its categories and routines could become resistant to revision. Here, the focus shifts to the people being administered. Their knowledge and behavior do not remain fixed under intervention; they interpret, adapt to, and sometimes resist the categories imposed on them. The instability at issue is therefore not only a weakness in institutional correction but also a consequence of the adaptive agency of the people whose behavior the institution seeks to make predictable.

When Representation Becomes Reality

Institutions have strong reasons to reduce uncertainty. Large organizations cannot function without categories, procedures, indicators, reports, classifications, and professional routines. The difficulty arises when these instruments become more resistant to revision than the circumstances they were designed to address.

A mismatch develops when established categories gradually lose correspondence with evolving circumstances.

The institutional response is often to increase administrative sophistication. More classifications are introduced. More reporting requirements are created. More data are collected. More specialized personnel are assigned. More indicators are developed. More information systems are built.

The institution becomes more elaborate in its efforts to be more responsive. Yet greater complexity does not necessarily translate into greater corrective capacity.

It may produce the opposite.

Every new procedure introduces another element that must be maintained. Every new category establishes another boundary that information must cross. Every new reporting requirement generates another stream of information that someone must interpret. Every new technological system creates new dependencies on the assumptions embedded within it.

The institution may consequently become better at processing representations but worse at questioning the assumptions underlying those representations.

When that mismatch persists, institutions may respond by adding administrative mechanisms rather than revising the assumptions underlying their categories.

The result can be an institution that becomes increasingly elaborate and increasingly distant from the reality it was created to manage.

Responsiveness Is Not Corrigibility

This distinction is central to the argument.

An institution can appear highly responsive while becoming progressively less able to correct its actions. It can respond to criticism by producing a report, establishing a consultation, commissioning a review, collecting additional data, creating a new committee, introducing another procedure, or developing a more sophisticated algorithm.

From the outside, all of this may appear to be learning.

But none of these actions necessarily changes the assumptions that produced the original problem.

Responsiveness and corrigibility are therefore not identical.

Responsiveness concerns an institution’s capacity to respond to information requests.

Corrigibility concerns its capacity to change itself in response to what it learns.

The difference is crucial.

An institution can listen without learning. It can consult without correcting. It can measure without reconsidering. It can reform its procedures without reexamining the institutional assumptions that produced them.

This is one way administrative expansion can occur without producing correction.

Information continues to enter the system, but it is increasingly interpreted through categories the system is reluctant or unable to revise.

The problem is no longer simply a matter of insufficient information.

Knowledge can enter the institution without being able to change it. That is a much more serious problem.

More Information, Less Knowledge

The digital age makes this distinction especially difficult to discern because technological sophistication can create the appearance of epistemic mastery.

A surveillance system can identify patterns in past behavior. An algorithm can detect correlations that would otherwise go unnoticed. A digital identity system can simplify transaction monitoring and rule enforcement. Artificial intelligence can dramatically expand the capacity for classification and prediction.

All of these developments can enhance administrative capacity, but none of them eliminates the underlying epistemic problem.

The individuals being observed remain capable of learning from the system. They adapt to it, identify its blind spots, adjust their strategies, cooperate with one another, and reinterpret the categories imposed on them. They sometimes develop behaviors that the original models did not anticipate.

More surveillance can therefore yield more information without yielding proportionally more knowledge.

This distinction is essential.

Information is something a system can accumulate.

Knowledge, in the Hayekian sense, is tied to circumstances, interpretation, action, and discovery. The accumulation of data does not guarantee that an institution knows what the data mean, which facts matter, or how its decisions should change.

Indeed, data accumulation can create a new form of institutional dependence.

The more procedures a system creates, the more resources it must invest to maintain them. The more categories it establishes, the harder it becomes to abandon them. The more data it accumulates, the greater the authority that may be granted to the models interpreting it.

Complexity can therefore begin to shield the institution from the very knowledge it was designed to handle.

The Paradox of Total Control

The aspiration for comprehensive control makes this problem particularly apparent.

A fully administered society would require an extraordinary degree of predictability. It would need to anticipate how individuals would respond to incentives and restrictions, which alternatives they would pursue, how they would interact with one another, and how those interactions would shape subsequent behavior.

But these are precisely the kinds of knowledge that cannot be fully specified in advance.

The problem is not simply that technology is insufficiently advanced.

The problem is that the controlled object is adaptive.

A surveillance system can observe behavior, but it cannot permanently fix its meaning. An algorithm can identify a pattern, but it cannot guarantee that the pattern will remain valid once people begin responding to it. A government can impose a rule, but it cannot fully determine how individuals will interpret, evade, comply with, resist, or strategically exploit it.

The more comprehensive the control system becomes, the more it alters the environment to which people respond.

And the more people adapt to that environment, the more quickly the assumptions underlying the system can become obsolete.

The paradox is therefore straightforward: attempts to eliminate human uncertainty can create new forms of uncertainty.

But the deeper paradox is even more profound.

Attempts to eliminate human autonomy can create precisely the forms of adaptation and resistance that make human behavior harder to predict.

The Prison Planet Illusion

This is why the idea of a fully administered “Prison Planet”—used here as shorthand for a society governed by pervasive surveillance, classification, and behavioral control—seems less stable than it appears to be.

A technologically sophisticated system could monitor vast amounts of human activity. It could identify individuals, track transactions, analyze communications, predict probabilities, restrict movement, automate decisions, assign risk scores, and impose consequences at unprecedented speed.

These are real capabilities and should not be dismissed. But powerful instruments of control do not imply the possibility of achieving complete control.

A genuine Prison Planet would require something far more demanding than comprehensive surveillance. It would require human beings to remain sufficiently predictable even after the system had altered the conditions of their lives.

That is precisely what cannot be guaranteed.

The people within the system would continue to learn from it. They would adapt to its rules, identify its blind spots, build relationships, develop strategies, reinterpret imposed categories, and seek ways to preserve autonomy and meaning.

They would not necessarily resist in dramatic or organized ways. Human adaptation can be far more subtle. People can adjust routines, reinterpret instructions, find workarounds, cooperate informally, disengage psychologically, conceal their intentions, or learn to navigate the institutional environment more effectively.

From the system’s perspective, however, each adaptation introduces a new prediction problem. The apparent solution, in turn, creates another problem.

The more comprehensive the system becomes, the more it must monitor the consequences of its interventions. The more it monitors, the more it alters the environment. The more the environment changes, the more its models require revision.

The system becomes caught in an endless attempt to stabilize what its own interventions continually destabilize.

The Prison Planet is therefore not impossible merely because technology is limited.

It is unstable because the human beings inside it remain human.

Vietnam: Escalation, Adaptation, and Institutional Failure

The Vietnam War offers a historical illustration of the Human Instability Principle. American intervention repeatedly altered the political and military environment in which Vietnamese actors operated. Their responses, in turn, changed the conditions confronting American policymakers, often undermining the assumptions underlying earlier decisions. Rather than reliably restoring control, successive interventions generated new problems that invited further intervention. The resulting pattern can be represented as a feedback loop: intervention → adaptation → instability → renewed intervention.

Daniel Ellsberg’s experience within the American policy apparatus offers a revealing perspective on this dynamic. His work on the classified history, later known as the Pentagon Papers, exposed a recurring pattern of official deception and escalation across administrations.

Policymakers continued to pursue the war despite mounting evidence, internal doubts, and repeated failures to achieve their stated objectives. Ellsberg released the documents to make that history public and to help end the war (”Pentagon Papers, Watergate and Trials”). His stated purpose was not to formulate the Human Instability Principle but to expose decisions and deceptions that had kept the American public from understanding the war it was being asked to support.

The broader theoretical implication follows from the evidence without needing to be attributed to Ellsberg. When an institution interprets the consequences of its interventions primarily as reasons to intervene further, it can become trapped in a cycle in which its attempts to restore control reproduce the conditions that led to its failure.

The problem is not simply that policymakers lack information. Rather, new information and changing circumstances do not necessarily prompt them to revise the assumptions that guide their decisions. In such a situation, escalation can substitute for correction, and each additional intervention alters the environment the institution seeks to control.

The Vietnam example, therefore, illustrates a central proposition of the Human Instability Principle: efforts to impose control over an adaptive environment can generate further instability when the institution fails to learn from the consequences of its actions.

Institutional Closure

None of this necessarily leads to institutional collapse.

An institution that has accumulated layers of administrative procedures can continue operating for a very long time. It can employ experts, produce reports, collect enormous amounts of data, refine algorithms, establish oversight mechanisms, and develop increasingly sophisticated surveillance systems.

The crucial change is in its capacity for correction.

Internal coherence becomes increasingly important. Established categories become increasingly difficult to abandon. Knowledge emerging outside those categories becomes increasingly difficult to translate into institutional change.

This is the deeper meaning behind institutional closure.

Closure does not mean that an institution receives no information. It means that information can circulate widely without sufficient force to revise the categories through which the institution interprets reality.

A closed system can therefore appear remarkably active.

It can continuously produce decisions, reports, consultations, reforms, metrics, and policy adjustments. Its problem is not inactivity. Its problem is that activity can occur without fundamental correction.

An institution can change constantly while remaining structurally unchanged.

This distinction also helps explain why institutional rigidity does not necessarily stem from incompetent or malicious individuals.

People working within a closed structure can be conscientious, intelligent, and genuinely committed to solving problems. Yet their actions are constrained by the categories, procedures, incentives, and responsibilities the institution uses to process information.

The problem can therefore lie less in individuals’ intentions than in the structure through which those intentions must operate.

That is why adding more intelligence to an institution does not necessarily make it more corrigible.

The issue is not simply about who makes the decisions.

It is whether the institutional structure permits inconvenient knowledge to change the assumptions underlying decisions.

Disagreement, Resistance, and Discovery

This is also why disagreement should not be automatically treated as a flaw in an administrative system.

Norman R. F. Maier and L. Richard Hoffman demonstrated experimentally that disagreement within groups can either trigger defensiveness or foster more innovative solutions, depending in part on how leaders interpret and manage it.

When disagreement is treated as evidence of “problem employees,” innovation and acceptance suffer; when dissenters are treated as sources of ideas, solution quality can improve.

The broader lesson is important for institutional systems. A disagreement may be noise.

But it may also be information. Resistance may indicate obstruction.

But it may also reveal that an institutional representation does not adequately reflect the circumstances of those affected by its decisions.

The difficulty is that a closed institution has incentives to interpret inconvenient information through the lens of its existing categories.

A dissenter can therefore be deemed “non-compliant.”

A dissatisfied participant can become “difficult.”

An unexpected outcome can be treated as an exception.

A failure of the institutional model can serve as evidence that the population requires closer monitoring or regulation.

This creates a dangerous possibility: the system may interpret evidence of its limitations as a sign that more of the same is needed.

At that point, correction becomes increasingly difficult.

The institution no longer asks whether its categories are inaccurate.

It asks how to enforce them more effectively.

The Ultimate Limit of Administration

None of this means that centralized institutions are incapable of exercising real control. States can restrict movement, monitor communications, impose penalties, regulate transactions, and make certain behaviors more costly. Technology can extend the reach and precision of these measures.

The argument is narrower: greater administrative capacity does not eliminate the knowledge problem that arises because those being governed continue to learn, adapt, and generate knowledge through their responses.

Mises’s work on economic calculation, Hayek’s account of dispersed knowledge, and Kirzner’s emphasis on discovery illuminate different aspects of this limitation. The Human Instability Principle extends these insights to comprehensive administration.

Those who possess and generate relevant knowledge are not passive objects outside the system; they are adaptive participants within it. A system can learn from them only if the knowledge they generate can alter the categories and assumptions that guide its actions.

Once those categories become effectively immune to revision, information may continue to accumulate, making correction increasingly difficult.

This is institutional closure: not the absence of information, but the inability of information to change the framework that interprets it. The institution may remain active and powerful, yet become less able to understand why people do not behave as its models predict.

The ambition of total administration therefore contains a contradiction. It seeks to make behavior predictable while altering the conditions that produce it; it seeks to eliminate uncertainty while relying on categories that must be revised as people adapt.

Its weakness need not manifest as collapse. Instead, it may appear as more elaborate procedures, more data, greater surveillance, and repeated attempts to manage the consequences of earlier interventions.

The Human Instability Principle is not a claim that human beings cannot be influenced or governed. It is a claim that they cannot be transformed into permanently stable administrative variables without disregarding the adaptive agency through which they interpret circumstances, discover possibilities, and respond to power. The more completely a system tries to suppress this instability, the more likely it is to encounter it again as a consequence of its own actions.

Annotated MLA Bibliography

Hayek, F. A. “The Use of Knowledge in Society.” The American Economic Review, vol. 35, no. 4, 1945, pp. 519–530.

Hayek’s essay provides the principal epistemological foundation for the Human Instability Principle. Its central insight is that the knowledge required for social coordination is dispersed, contextual, and often unavailable in full to any central authority. The present essay extends that argument beyond economic coordination: when the object of administration comprises adaptive human beings, the relevant knowledge not only remains dispersed but also changes as individuals respond to institutional intervention.

Kirzner, Israel M. Competition and Entrepreneurship. University of Chicago Press, 1973.

Kirzner is invoked here to introduce the idea of knowledge as discovery rather than as a fixed stock of information waiting to be collected. His conception of entrepreneurial alertness is particularly relevant to the Human Instability Principle because individuals not only possess information unknown to administrators but also continually discover opportunities, errors, and possibilities through action. The essay generalizes this insight to administrative systems: human beings can discover possibilities that institutional models did not anticipate.

Maier, Norman R. F., and L. Richard Hoffman. “Acceptance and Quality of Solutions as Related to Leaders’ Attitudes toward Disagreement in Group Problem Solving.” The Journal of Applied Behavioral Science, vol. 1, no. 4, 1965, pp. 373–386.

Maier and Hoffman’s experimental study supports the essay’s argument about disagreement and institutional learning. Their findings suggest that disagreement can become a source of innovation when treated as potentially informative rather than automatically dismissed as a problem. The study is therefore useful for distinguishing between systems that treat resistance as information and those that neutralize dissent by labeling dissenters as problematic participants.

“Pentagon Papers, Watergate and Trials.” The Daniel Ellsberg Papers, University of Massachusetts Amherst, www.umass.edu/ellsberg/featured-documents/pentagon-papers-watergate-and-trials/. Accessed 10 Oct. 2026.

This archival account documents the background of the Pentagon Papers and Ellsberg’s stated aim of informing the public in the hope of helping end the war. It supports the historical description in the Vietnam section; the interpretation of intervention and adaptation as a feedback loop is the present essay’s analytical extension.

Mises, Ludwig von. “Economic Calculation in the Socialist Commonwealth.” Collectivist Economic Planning, edited by F. A. Hayek, Routledge & Kegan Paul, 1935, pp. 87–130.

Mises’s essay establishes that technical knowledge of resources and production methods cannot, by itself, resolve the problem of allocating scarce resources among competing uses. It grounds the present essay’s discussion of economic calculation; the extension to adaptive human behavior is the author’s argument, not a claim Mises makes in these terms.

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