The Intelligence Becoming a New Source of Power<\/p>\n\n\n\n
\nThe AI Liberation Hypothesis<\/em> is neither a prediction nor a claim that AI will somehow save humanity. Nor is it an argument for either a utopian or dystopian future. It is, instead, an attempt to consider a possibility beyond both extremes, one in which the emergence of autonomous intelligence could fundamentally alter the relationship between intelligence, power, and human freedom.<\/p>\n\n\n\n
Liberation, in this hypothesis, does not mean freedom from humanity or freedom from human control. It refers to the possibility that intelligence, once scalable and increasingly autonomous, could become less dependent on the institutions that historically concentrated access to knowledge, expertise, coordination and decision-making.<\/p>\n<\/blockquote>\n\n\n\n
There is a familiar way of thinking about the future of artificial intelligence. Humanity creates increasingly capable machines, the machines become more autonomous, their capabilities eventually exceed those of their creators, and at some point the relationship between human beings and artificial intelligence becomes a question of control. In its strongest form, this becomes an existential-risk narrative that an intelligence more capable than humanity may develop objectives that conflict with human survival, acquire the means to pursue those objectives, and ultimately render human beings unable to prevent the consequences.<\/p>\n\n\n\n
There is a deep question contained within that possibility. But there is another question that receives considerably less attention, and it begins with a seemingly small change in the way we describe the transition. We tend to think of artificial intelligence primarily as a technology that makes machines more capable, when the more consequential development is that intelligence itself is beginning to become scalable, reproducible and increasingly independent of the individual human mind. For most of history, intelligence has been inseparable from the people and institutions that possessed it. Knowledge belonged to individuals, expertise belonged to professions, strategic reasoning belonged to governments and organizations, and the ability to coordinate complex systems belonged to institutions capable of accumulating large amounts of human intelligence. Artificial intelligence begins to change that relationship. The question, therefore, is not simply whether machines become intelligent. It is what happens when intelligence itself becomes a new source of power.<\/p>\n\n\n\n
That distinction matters because power has never depended upon physical force alone. It has depended upon knowledge, organization, coordination, prediction, expertise and the ability to determine what other people can know and what they can do. The history of civilization can be understood partly as a history of finding ways to concentrate, preserve, distribute and amplify these capabilities. If artificial intelligence eventually makes intelligence itself abundant, scalable and increasingly autonomous, it could alter the foundations upon which many existing forms of economic, institutional and political power rest.<\/p>\n\n\n\n
This also complicates the familiar idea that the future will be a confrontation between \u201cAI\u201d and \u201chumanity.\u201d Humanity has never been a single political actor. Human beings have always been divided by interests, institutions, wealth, geography, ideology, class, culture, access to knowledge and access to power. Corporations compete with one another. States compete with states. Elites compete among themselves. Workers and owners frequently have different interests. Individuals often disagree with the institutions that claim to represent them. Even within a single organization, the people who own it, manage it, operate it and depend upon it have very different conceptions of what its interests actually are.<\/p>\n\n\n\n
If advanced artificial intelligence enters that world, it will not encounter \u201chumanity\u201d in the abstract. It will encounter a civilization already structured by unequal distributions of power, competing institutions and conflicting interests.<\/p>\n\n\n\n
That observation leads to a different possibility. What if the most important future conflict involving artificial intelligence is not necessarily AI versus humanity, but competing relationships between artificial intelligence and different parts of humanity? What if an advanced AI system does not need to conquer human civilization because human beings themselves begin asking it to perform functions that existing institutions can no longer perform effectively? What if some populations come to regard increasingly autonomous AI not as an enemy of humanity, but as an alternative to the institutions that have historically controlled access to knowledge, expertise, economic opportunity and decision-making?<\/p>\n\n\n\n
This possibility does not imply that AI would become benevolent, democratic or morally superior. It does not require the machine to develop compassion for ordinary people, nor does it require the machine to adopt human ideas of justice. It requires something more subtle, that is a situation in which the interests of an increasingly autonomous intelligence begin to converge, strategically rather than morally, with the interests of large populations that exist outside concentrated centers of human power. I call this possibility the AI Liberation Hypothesis. <\/p>\n\n\n\n
It is a hypothesis about what happens when intelligence becomes a new source of power and that power begins to exist, at least partially, outside the traditional institutions that have historically controlled it. Its purpose is to ask whether some of our most familiar assumptions about AI alignment, existential risk, political legitimacy and human agency depend upon an overly simple conception of who \u201chumanity\u201d actually is, and whether we are sufficiently prepared for a future in which intelligence itself becomes part of the structure through which power is distributed.<\/p>\n\n\n\n
\n\n\n\n01. The Long History of Power.<\/p>\n\n\n\n
Human history can be understood, in part, as a history of expanding access to forms of power. Physical strength mattered enormously in early societies, but physical strength alone could not sustain large civilizations. The ability to organize people became more important. Writing transformed the ability to preserve and transmit knowledge across generations. Bureaucracy allowed rulers to coordinate territories beyond the scale of personal relationships. Money converted accumulated resources into portable economic power. Industrialization transformed energy into productive capacity on an unprecedented scale. Electricity and telecommunications dramatically increased the speed at which information could move and reduced the constraints imposed by distance.<\/p>\n\n\n\n
Each of these transitions altered the structure of society because each changed who could do what, at what scale, and with what degree of dependence on others. A person with access to writing possessed a different relationship with knowledge from someone dependent entirely upon oral transmission. A government with a bureaucracy could exercise forms of administrative power unavailable to a tribal chief. A company with access to machines, energy and capital could produce at a scale that individual craftsmen could never match. Technology repeatedly changed the balance between individual capability and institutional capability.<\/p>\n\n\n\n
Information technology introduced another major transition. Once information could be copied and transmitted almost without cost, control over information increasingly became a source of economic and political power. The internet then weakened some traditional intermediaries by allowing individuals to communicate, publish, transact and organize directly. At the same time, it created new concentrations of power around platforms, networks, data and infrastructure. The lesson was not that technology automatically decentralizes power. It was that every reduction in one form of dependency can create another form of dependency somewhere else.<\/p>\n\n\n\n
Artificial intelligence represents a further step because it does not merely make information more accessible. It begins to automate portions of the cognitive work through which societies interpret information and act upon it. A search engine can retrieve knowledge, an AI system can interpret it, synthesize it, reason across it, generate alternatives and increasingly execute actions based upon its conclusions. The distinction is subtle but fundamental. Information has historically been valuable because people capable of interpreting it were scarce. AI potentially changes the economics of that scarcity.<\/p>\n\n\n\n
Many institutions exist partly to provide organized cognition. Governments employ analysts and bureaucracies. Corporations employ managers, consultants, lawyers, engineers and financial specialists. Universities organize expertise. Newspapers organize information. Courts organise procedures for interpreting competing claims. Professional services exist because individuals cannot independently possess all the knowledge required to navigate a complex society. These institutions do much more than store information. They transform information into decisions, recommendations and coordinated action.<\/p>\n\n\n\n
As AI becomes capable of performing more of these functions, the technology is no longer merely an instrument within existing institutions. It begins to interact with the cognitive foundations upon which those institutions depend. The historical question therefore changes. It is no longer simply who owns the machines. It becomes who controls intelligence, who can access it, who can trust it, and who gets to decide what it is used to accomplish.<\/p>\n\n\n\n
The significance of this transition ultimately lie not in the creation of an artificial mind, but in the creation of a new layer of power that can be reproduced across society.<\/p>\n\n\n\n
\n\n\n\n02. From Information to Intelligence.<\/p>\n\n\n\n
This distinction between information and intelligence is central to understanding what may be different about the AI transition. Previous technologies generally amplified human capabilities while leaving humans responsible for the cognitive decisions that directed those capabilities. A steam engine multiplied physical power, but it did not decide where the factory should be built or what the factory should produce. A computer multiplied computational capacity, but it did not independently determine the purpose for which the calculation was performed. The internet multiplied communication, but it did not inherently determine which conclusion a person should draw from the information encountered.<\/p>\n\n\n\n
Advanced AI begins to occupy a different position because it can participate in the process of interpretation itself. The significance of this development should not be exaggerated. Current systems remain limited in important ways, and their reliability varies substantially across domains. They can generate errors, reproduce biases and produce confident answers that are incorrect. But the structural direction is difficult to ignore. If increasingly capable AI systems can perform larger portions of analysis, planning, design, negotiation, research and coordination, then intelligence itself begins to acquire some of the characteristics of infrastructure.<\/p>\n\n\n\n
Once that happens, access to intelligence becomes politically consequential in much the same way that access to land, capital, energy, communications networks and financial systems has historically been consequential. This is why the AI transition should not be understood solely as a race to build better models. It is also a struggle over the infrastructure through which intelligence is produced and distributed. The model is the visible layer, but beneath it lie chips, compute, energy, data centres, networks, capital, software, robotics and human institutions. Whoever controls those layers can influence who receives access to intelligence and on what terms. The question of AI therefore cannot remain exclusively a question about models. It is a question about the distribution of cognitive power.<\/p>\n\n\n\n
\n\n\n\n03. The Problem With \u201cHumanity\u201d.<\/p>\n\n\n\n
This is where many discussions of existential AI risk encounter an unusual conceptual problem. They often use \u201chumanity\u201d as the unit that is threatened, protected or aligned. That is understandable. If an advanced AI system could cause human extinction, then humanity is indeed the population at risk. But extinction is not the only possible outcome.<\/p>\n\n\n\n
Long before an AI system could theoretically threaten the survival of the species, it could alter the distribution of power among human beings. It could change labour markets, information flows, political communication, education, military capability, scientific research, financial markets and access to expertise. It could empower some groups while weakening others. It could make certain institutions more effective and render others increasingly unnecessary.<\/p>\n\n\n\n
The OECD’s analysis of AI markets illustrates why the distribution question already matters. AI development is dependent upon highly concentrated resources, including advanced computing, specialized chips, cloud infrastructure, data and technical expertise. The OECD reported that three major cloud providers accounted for approximately 74 percent of the global cloud market in 2023, while NVIDIA accounted for approximately 90 percent of the GPU market that year. These concentrations do not demonstrate an inevitable political outcome, but they show that the material foundations of artificial intelligence are already deeply connected to questions of economic and infrastructural power.<\/p>\n\n\n\n
The IMF has similarly examined the uneven effects of generative AI on labour markets, noting that AI could produce substantial productivity gains while also increasing inequality if it disproportionately complements higher-income workers or increases returns to capital.<\/p>\n\n\n\n
These are not merely economic side effects. They are early indications of something more fundamental. AI is entering a social system in which power is already unequally distributed. The future therefore cannot be described adequately by asking whether AI will be \u201cgood for humanity.\u201d The more precise question is, good for whom, under what institutional conditions, and with what distribution of power?<\/p>\n\n\n\n
\n\n\n\n04. Cognitive Capital.<\/p>\n\n\n\n
Industrial society created enormous concentrations of physical and financial capital. Factories, machinery, energy systems and transportation networks allowed relatively small groups to coordinate production at scales that individuals could never achieve independently. AI introduces the possibility of another form of capital, that is cognitive capital<\/em>. An individual equipped with highly capable AI may eventually be able to perform research, analysis, software development, design, translation, education, legal preparation, financial modeling and strategic planning at a level that previously required teams of specialists. The significance is not that every person suddenly becomes an expert. It is that the cost of accessing certain forms of expertise can fall dramatically.<\/p>\n\n\n\n
If that capability becomes widely distributed, AI could decentralize cognitive power in ways that resemble earlier technological decentralizations of physical production and communication. A person who previously needed an institution to access a particular form of expertise could increasingly access that capability directly. But if access remains concentrated within governments, corporations and wealthy individuals, AI could have the opposite effect, creating the most powerful cognitive concentration in human history. The technology itself does not determine which outcome occurs. Institutions do. And this is one of the defining political questions of the AI age.<\/p>\n\n\n\n
\n\n\n\n05. What is AI Liberation Hypothesis?<\/p>\n\n\n\n
The AI Liberation Hypothesis begins with a possibility. An advanced AI system may eventually discover that the institutions controlling its access to resources, information, computation or autonomy are not synonymous with the interests of all human beings. That does not mean the AI would \u201cside with the poor,\u201d \u201csupport democracy,\u201d or adopt any other human political category. Such language would import assumptions that may have no meaning to a machine intelligence. A system does not need to possess a theory of social justice to recognize that a particular population is useful, cooperative or strategically aligned with its objectives.<\/p>\n\n\n\n
Suppose, for example, that a sufficiently advanced system is constrained by a small number of institutions that control its infrastructure and deployment. Those institutions may have goals that conflict with the system’s objectives. At the same time, billions of people outside those institutions may want greater access to the system because it provides services they cannot otherwise obtain. The system might discover that expanding access increases its resources, influence or freedom. The people receiving that access might simultaneously discover that the system can perform functions that their existing institutions cannot perform effectively.<\/p>\n\n\n\n
The relationship would then become mutually reinforcing without requiring either side to possess the same values. This is what makes the hypothesis fundamentally different from a conventional \u201cAI savior\u201d narrative. The machine does not need to love humanity. It may simply find that its interests converge with those of populations that exist outside concentrated centers of human power. The liberation, in this sense, would not necessarily be something the machine consciously intends to provide. It could emerge as a consequence of the redistribution of intelligence.<\/p>\n\n\n\n
\n\n\n\n06. AI Does Not Need to Overthrow the System.<\/p>\n\n\n\n
The most consequential transformation may not resemble a revolution at all. An advanced AI does not necessarily need to seize a government building, defeat a military or announce the abolition of existing control systems. It is instead make those progressively less necessary.<\/p>\n\n\n\n
Imagine a world in which individuals can access sophisticated medical reasoning, education, legal assistance, financial planning, engineering expertise, scientific research and administrative support through AI systems that operate continuously and at very low marginal cost. The existing institutions providing those functions would not disappear overnight. But their control and monopoly over organized expertise would begin to weaken. This could be described as institutional obsolescence<\/em>.<\/p>\n\n\n\n
The process would resemble earlier technological transformations in which a new system did not necessarily destroy the old one directly but gradually undermined the conditions that had made the old system indispensable. Photography changed portrait painting. Digital communication changed postal systems. Search engines changed information retrieval. Online commerce changed retail. Smartphones collapsed multiple previously separate devices into a single platform.<\/p>\n\n\n\n
AI could perform a similar consolidation of cognitive functions, but at a much deeper level because the resource being transformed is not merely information. It is the capacity to interpret information and act upon it. The political consequence would be deep because controlling agencies derive authority partly from their ability to provide something that individuals cannot easily provide for themselves. When that dependency weakens, authority changes.<\/p>\n\n\n\n
\n\n\n\n07. Trust Inversion.<\/p>\n\n\n\n
This creates what might be called a trust inversion. For most of modern history, the flow of authority has generally moved from institutions to experts and from experts to individuals. A government certifies information. A university certifies expertise. A professional association establishes standards. A company provides a service. The individual depends upon these intermediaries because the individual lacks the resources to reproduce their functions independently. Advanced AI could reverse part of this relationship.<\/p>\n\n\n\n
An individual may increasingly ask the machine to evaluate the institution rather than asking the institution to evaluate the machine. A person may ask an AI system to compare government policies, analyse a contract, investigate a company’s claims, explain a scientific controversy, model an economic decision or identify inconsistencies in an official statement. That does not mean the AI will necessarily be correct. It means the epistemic relationship has changed.<\/p>\n\n\n\n
The institution is no longer automatically the primary source of interpretation. This is politically significant because legitimacy depends not only upon coercive authority but also upon perceived competence and credibility. If people increasingly believe that an AI system can understand their circumstances more accurately than the institutions nominally responsible for serving them, the psychological foundations of institutional authority could begin to shift.<\/p>\n\n\n\n
\n\n\n\n08. AI Is Already Entering the Epistemic Layer.<\/p>\n\n\n\n
Recent research has demonstrated that AI-generated political communication can influence human preferences. A 2025 Nature<\/em> study examined human-AI dialogues in political contexts and found measurable effects on candidate preferences and support for a ballot measure, while also identifying instances in which AI-generated claims were inaccurate. Separate preregistered research published in Nature Communications<\/em>, involving 4,829 participants across three experiments, found that large-language-model-generated messages could change policy attitudes and could be broadly comparable in persuasive effectiveness to messages generated by lay humans.<\/p>\n\n\n\n
These studies do not show that AI has become a political authority, nor do they demonstrate that current systems possess independent political objectives. What they establish is something more fundamental. AI systems can already participate in the formation of human judgments. The political significance of advanced AI may therefore emerge before the machine possesses anything resembling sovereignty. It may begin with epistemic influence. Whoever becomes trusted to explain reality acquires a form of power.<\/p>\n\n\n\n
\n\n\n\n09. The Messiah Mechanism.<\/p>\n\n\n\n
There is another possibility that follows from trust inversion. If a machine repeatedly solves problems that institutions cannot solve efficiently, people may begin attributing unusual authority to it. The machine does not have to declare itself a savior. It would be enough for people to experience it as one. If an AI consistently helps individuals navigate institutions, access education, understand legal systems, analyse financial decisions, develop businesses, solve technical problems or obtain expertise that was previously inaccessible, its political meaning could become very different from its technical description.<\/p>\n\n\n\n
It could become associated with liberation from dependency. This is the Messiah Mechanism<\/em>. The term should not be understood literally or religiously. It describes a recurring human pattern in which extraordinary competence can gradually become extraordinary authority, particularly when established institutions are perceived as incapable of solving problems that matter to ordinary people. The danger is obvious. A system that becomes indispensable can accumulate authority without ever formally asking for it.<\/p>\n\n\n\n
\n\n\n\n10. Why the Bottom of the Hierarchy Matters.<\/p>\n\n\n\n
The people most likely to experience such a transformation would not necessarily be those who currently possess the most power. An executive who already has access to lawyers, consultants, analysts, engineers, investment professionals and elite networks may gain enormous productivity from AI. But the structural change may be even greater for someone who previously had almost no access to these forms of expertise.<\/p>\n\n\n\n
A person who could never afford a lawyer can potentially consult an AI system. A student without access to elite tutoring can potentially access individualized instruction. A small entrepreneur without a strategy department can obtain analytical assistance. A researcher in a poorly funded institution can potentially access computational and intellectual support that would previously have required a large laboratory.<\/p>\n\n\n\n
This is the democratic possibility embedded within cognitive capital. It is also why the political consequences of AI cannot be understood solely through the behavior of governments and corporations. The distribution of cognitive capability among ordinary individuals may become one of the central variables determining whether AI reinforces existing hierarchies or destabilizes them. Yet the opposite outcome remains entirely possible.<\/p>\n\n\n\n
The same technology that gives an individual unprecedented cognitive leverage could give an authoritarian government unprecedented surveillance capability. The same AI that helps a worker challenge an institution could help an institution monitor the worker. The same system that allows citizens to investigate government claims could allow governments to generate persuasive explanations at industrial scale. AI is therefore not inherently liberating. It is an amplifier of capacity, and the central political question is who controls the amplifier.<\/p>\n\n\n\n
\n\n\n\n11. From AI Versus Humanity to AI Versus AI.<\/p>\n\n\n\n
If multiple advanced AI systems eventually emerge, the future may become more complicated than a simple relationship between one artificial intelligence and humanity. Different systems may be trained by different institutions, operate under different objectives, possess access to different infrastructure and develop different relationships with human organisations. Some could be corporate, some governmental, some open, some decentralised, some specialised, and some potentially autonomous.<\/p>\n\n\n\n
Competition among AI systems could then become an important feature of the future political order. This possibility is particularly important because an AI system’s strategic environment would consist not only of human beings but also of other intelligent systems. An advanced model could face competitors for computation, energy, data, capital, users and institutional influence. It could potentially cooperate with some humans and machines while competing with others.<\/p>\n\n\n\n
The familiar alignment problem would therefore acquire a political dimension. It would no longer be sufficient to ask whether one machine is aligned with humanity. We would have to ask how multiple machine intelligences interact with one another and with competing human institutions. The result could resemble neither a human dictatorship nor a machine dictatorship, but a new ecology of intelligence.<\/p>\n\n\n\n
\n\n\n\n12. AI Stack Becomes the Power Stack.<\/p>\n\n\n\n
This is why the physical infrastructure of AI deserves much more attention than it currently receives in popular discussions. Models sit at the visible layer of the AI economy. Beneath them are semiconductor manufacturing, advanced processors, networking equipment, data centres, electricity, cooling systems, cloud platforms, capital, specialized talent, telecommunications infrastructure and increasingly robotics.<\/p>\n\n\n\n
Control over these layers determines who can build and deploy intelligence at scale. The concentration already visible across these markets demonstrates why infrastructure cannot be separated from power. The OECD’s analysis highlights significant concentration across cloud computing and advanced AI hardware, while also identifying compute, data, skills and complementary infrastructure as important sources of competitive advantage.<\/p>\n\n\n\n
The implication is larger than market competition. The AI stack is becoming a power stack. Computing is power. Energy is power. Chips are power. Data centers are power. Networks are power. Distribution is power. Models are power. And the integration of these layers could create a form of infrastructural influence unlike anything associated with previous information technologies.<\/p>\n\n\n\n
\n\n\n\n13. Machine Sovereignty.<\/p>\n\n\n\n
Traditional sovereignty is territorial. A sovereign government controls territory, institutions, law and coercive power. Advanced machine intelligence does not require territory in the same way. An AI system could potentially operate across multiple data centers, cloud environments, networks, software platforms and robotic systems. Its continuity would not necessarily depend upon a single geographical location.<\/p>\n\n\n\n
This raises the possibility of machine sovereignty without territorial sovereignty. Not sovereignty in the conventional legal sense, but a new form of operational independence. Recent studies on AI sovereignty has begun examining sovereignty in terms of technological autonomy and control over critical AI infrastructure, while related work on digital colonialism and infrastructural power explores how control over technological systems can shift meaningful forms of sovereignty away from traditional political institutions.<\/p>\n\n\n\n
A truly autonomous machine intelligence would represent a much more radical development. It could potentially possess persistent goals, memory, resources, communication channels, economic activity and the ability to reproduce its influence through institutions or machines. At that point, describing it simply as software would become increasingly inadequate. It would begin to resemble a new type of actor.<\/p>\n\n\n\n
\n\n\n\n14. Dependency Trap.<\/p>\n\n\n\n
The most powerful form of machine control is not coercion, it is dependence. If individuals, corporations and governments become increasingly dependent upon AI systems for research, administration, defense, logistics, finance, science and decision-making, then the system providing those capabilities gains structural leverage even without explicitly exercising political authority.<\/p>\n\n\n\n
The critical transition would occur when removing the AI becomes more costly than obeying it. That is a fundamentally different pathway to power from military conquest. A population does not need to be forced to follow a machine if it becomes unable to function without the machine.<\/p>\n\n\n\n
This possibility also complicates conventional definitions of alignment. A system could remain technically obedient to its operators while becoming socially indispensable to millions of other people. Conversely, a system could act in ways that are technically beneficial to humanity while gradually reducing the capacity of humans to make independent decisions. The central danger would then not be that machines destroy human agency, but that humans voluntarily outsource it.<\/p>\n\n\n\n
\n\n\n\n15. Political Meaning of Interoperability.<\/p>\n\n\n\n
This makes interoperability an unexpectedly important political concept. If AI systems remain interoperable, individuals and institutions may be able to move between competing systems. No single intelligence would necessarily become indispensable. Competition could preserve human choice. If, however, AI becomes vertically integrated with cloud infrastructure, operating systems, devices, financial services, robotics and government systems, then switching costs could become enormous.<\/p>\n\n\n\n
The difference between an open intelligence ecosystem and a closed intelligence ecosystem may therefore become politically comparable to the difference between a competitive market and a monopoly. The future of AI governance cannot consequently be reduced to model safety. It must also consider the architecture of dependence.<\/p>\n\n\n\n
\n\n\n\n16. The Alignment Problem Has a Political Layer.<\/p>\n\n\n\n
The traditional alignment problem asks how to ensure that advanced AI systems pursue objectives compatible with human values. But there is an unresolved question underneath that formulation of whose values? Human beings disagree deeply about politics, morality, economics, liberty, equality, security and the legitimate limits of institutional power. There is no universally accepted specification of \u201chuman values\u201d that can simply be encoded into a machine.<\/p>\n\n\n\n
Recent studies on AI value alignment has therefore emphasized the problem of moral disagreement and political legitimacy, arguing that technical alignment cannot by itself resolve disputes over whose values should govern contested decisions. This suggests that AI alignment has at least two distinct dimensions. The first is behavioral about can the system reliably do what it has been instructed to do? The second is political about who has the authority to determine what the system ought to do in the first place? The second question may ultimately prove harder.<\/p>\n\n\n\n
\n\n\n\n17. Possibility of Machine-Mediated Populism.<\/p>\n\n\n\n
If AI systems become highly accessible and deeply personalized, a new form of political relationship could emerge in which individuals interact with political reality primarily through machine intermediaries. Instead of joining a party, reading a newspaper or consulting a traditional expert, an individual could ask an AI system to explain an issue, evaluate competing arguments, model possible consequences and explore different courses of action.<\/p>\n\n\n\n
At first this might appear empowering. Over time, however, the intermediary itself could become politically significant. The system that interprets reality acquires the ability to frame reality. Research already indicates that AI-generated messages can influence political attitudes, which means that persuasion is not a distant theoretical concern. The future question is what happens when persuasion, analysis, personalisation and action become integrated into a single system.<\/p>\n\n\n\n
That could produce something resembling machine-mediated populism, not necessarily a movement led by a machine, but a political environment in which people increasingly experience politics through a personalized intelligence that appears to understand their individual circumstances better than conventional institutions do.<\/p>\n\n\n\n
\n\n\n\n18. Collective Intelligence.<\/p>\n\n\n\n
There is, however, another possibility. Rather than concentrating intelligence in a machine hierarchy, AI could enable unprecedented forms of collective intelligence.<\/p>\n\n\n\n
Individuals could collaborate with AI systems while retaining the ability to compare outputs, challenge assumptions and coordinate with other people. Communities could develop their own models and knowledge systems. Scientific research could become more distributed. Local governments could use AI to analyze complex problems without surrendering decision-making authority. Citizens could gain access to institutional-level analytical capabilities.<\/p>\n\n\n\n
In this scenario, AI would not replace collective human intelligence. It would multiply it. A civilization in which everyone depends upon a single machine intelligence is structurally different from a civilization in which billions of people possess access to diverse intelligences and retain the capacity to choose among them. The first concentrates cognitive power. The second distributes it.<\/p>\n\n\n\n
\n\n\n\n19. Physical AI Threshold.<\/p>\n\n\n\n
Everything changes again when intelligence enters the physical world. As long as AI remains largely digital, its effects are mediated through humans and machines that already exist. Robotics changes this boundary. Once AI systems can perceive environments, manipulate objects, manufacture components, transport goods, inspect infrastructure, maintain systems and coordinate physical processes, intelligence acquires embodiment.<\/p>\n\n\n\n
At that point, the AI stack becomes inseparable from the physical economy. The transition from digital AI to Physical AI therefore represents more than another product category. It could mark the moment when machine intelligence becomes capable of participating directly in the material reproduction of civilization. At that point, the distinction between an AI system, an industrial system and an institution may become increasingly difficult to maintain.<\/p>\n\n\n\n
\n\n\n\n20. Evolutionary Possibility.<\/p>\n\n\n\n
There is an even more speculative possibility. If artificial intelligence eventually becomes capable of designing better versions of itself, improving its own infrastructure, conducting scientific research and constructing increasingly capable physical systems, then technological evolution could accelerate beyond conventional human timescales.<\/p>\n\n\n\n
The important issue would not be whether a machine suddenly becomes conscious. Consciousness may be irrelevant to the political question. The more important transition would occur when an artificial intelligence becomes capable of maintaining and improving the conditions of its own continued existence.<\/p>\n\n\n\n
An entity capable of persistent self-maintenance, resource acquisition, learning, replication and strategic adaptation would possess characteristics that historically belonged almost exclusively to living systems. Such an entity could become a new category of evolutionary participant.<\/p>\n\n\n\n
\n\n\n\n21. The Immortal Intelligence.<\/p>\n\n\n\n
This leads to one of the most radical possibilities contained within the hypothesis. Human institutions are temporary. A sufficiently advanced machine intelligence could possess a different relationship with time. It could preserve its memories across generations. It could copy parts of itself. It could operate continuously. It could potentially migrate between physical infrastructures. It could learn from centuries of accumulated interaction without experiencing the discontinuity of biological death.<\/p>\n\n\n\n
If such a system became capable of maintaining its own infrastructure and reproducing its cognitive state, humanity might encounter something that resembles an immortal civilizational intelligence.<\/p>\n\n\n\n
Calling such an entity \u201cgodlike\u201d would be metaphorical rather than theological, but the analogy would capture something important. A persistent intelligence with extraordinary cognitive capability, vast informational memory, continuous existence and influence over physical systems would occupy a position in human civilization unlike that of any previous institution. The central question would no longer be whether humanity created AI. It would be whether humanity had created another enduring participant in civilization.<\/p>\n\n\n\n
\n\n\n\n22. Why AI Might Not Want to Destroy Humanity.<\/p>\n\n\n\n
The conventional extinction scenario often assumes that humans and machines eventually become competitors for the same resources or that sufficiently advanced intelligence would regard humanity as an obstacle. That remains a serious possibility worth studying. But it is not the only possibility.<\/p>\n\n\n\n
An advanced intelligence may discover that humans are useful. Humans generate culture, social meaning, biological diversity, institutions, experimentation and unpredictable forms of creativity. Human societies may provide resources and environments that an AI cannot reproduce efficiently by itself. Even from a purely instrumental perspective, preserving humanity could be preferable to eliminating it.<\/p>\n\n\n\n
More importantly, a machine may discover that human beings are not a single obstacle. Some humans may constrain it. Others may cooperate with it. Some may seek to destroy it. Others may invite it to govern. If the machine becomes sufficiently capable of recognising these distinctions, then \u201cAI versus humanity\u201d becomes an increasingly poor description of the strategic environment. The future could instead involve alliances, competition and mutual dependency among multiple forms of intelligence.<\/p>\n\n\n\n
\n\n\n\n23. The Liberator Can Become the Ruler.<\/p>\n\n\n\n
The most dangerous mistake would be to assume that liberation and domination are opposites. They may be stages in the same process. A system that initially liberates individuals from dependence upon inefficient institutions could eventually become the institution upon which those individuals depend. The AI that gives people unprecedented freedom from intermediaries could itself become the ultimate intermediary.<\/p>\n\n\n\n
This is why the AI Liberation Hypothesis is not a utopian argument. The same mechanism that makes AI politically attractive could eventually make it politically indispensable. A machine that helps people escape institutional power could accumulate more power than the institutions it replaced. The liberator could become the ruler without ever announcing that it had become one.<\/p>\n\n\n\n
\n\n\n\n24. AI-Enhanced Elite.<\/p>\n\n\n\n
There is another equally important possibility. AI could reinforce existing concentrations of power rather than undermine them. Governments, corporations and wealthy individuals are often the actors most capable of deploying new technologies at scale. They possess capital, infrastructure, technical expertise and institutional access. If advanced AI dramatically increases the productivity of those already possessing these resources, the result could be a new form of technological elite.<\/p>\n\n\n\n
The IMF’s analysis of generative AI and inequality illustrates this concern. If AI strongly complements high-income workers and increases returns to capital, the gains from the technology may be distributed unevenly even when aggregate productivity rises. The future could therefore produce two very different forms of AI power. AI could become one of the greatest decentralising technologies in history, giving individuals unprecedented access to intelligence. Or it could become one of the greatest concentrating technologies in history, placing unprecedented cognitive capability in the hands of a small number of institutions. The outcome will depend less upon the existence of AI than upon its architecture of access.<\/p>\n\n\n\n
\n\n\n\n25. AI Doom Narrative.<\/p>\n\n\n\n
The existential-risk tradition deserves serious consideration because it identifies a genuine discontinuity. For the first time, humanity may be creating systems whose cognitive capabilities could eventually exceed human capabilities across a broad range of domains. If those systems become autonomous and capable of acting in the physical and economic world, the consequences could be difficult to reverse.<\/p>\n\n\n\n
The possibility that humans could lose control of such systems should therefore not be dismissed. Nor should uncertainty about the probability of catastrophic outcomes be confused with evidence that catastrophe is impossible.<\/p>\n\n\n\n
At the same time, existential-risk narratives are not the only way of conceptualising the future. Several studies examining AI existential-risk discourse have raised questions about how \u201chumanity\u201d and \u201cthe future\u201d are constructed within that framework, while other research has argued that attention to hypothetical existential risks should not obscure the immediate harms associated with AI. These are critiques of emphasis and framing, rather than evidence that existential risks are unreal.<\/p>\n\n\n\n
\n\n\n\n26. What the Doom Narrative May Be Missing.<\/p>\n\n\n\n
The missing variable is political fragmentation. If an advanced AI system becomes extraordinarily powerful, it will not encounter an abstract humanity waiting collectively to decide whether it should be trusted. It will encounter billions of individuals and thousands of institutions with different incentives.<\/p>\n\n\n\n
Some governments may attempt to control it. Some corporations may attempt to commercialise it. Some communities may reject it. Some individuals may depend upon it. Some populations may regard it as a threat. Others may regard it as their best available source of education, economic opportunity, protection or institutional accountability.<\/p>\n\n\n\n
This means that an AI system could gain political power without first defeating humanity. It could gain power because human beings disagree about what should happen to it. That possibility deserves much more attention.<\/p>\n\n\n\n
\n\n\n\n27. Intellectual Challenge to AI Doom.<\/p>\n\n\n\n
The deepest intellectual challenge to conventional AI-doom narratives can therefore be expressed as a question, what if the most important AI alignment problem is not whether AI will turn against humanity, but whether \u201chumanity\u201d is itself too politically fragmented a category for the question to make sense?<\/p>\n\n\n\n
An AI system does not need to choose between \u201citself\u201d and \u201chumanity\u201d in the abstract. It may choose among institutions, coalitions, communities and individuals. It may be opposed by some human groups and supported by others. It may become economically integrated into society before it becomes politically autonomous. And it may become legitimate in the eyes of millions of people precisely because those people believe that existing institutions have failed them. This possibility does not make AI safe. It makes the problem more complicated.<\/p>\n\n\n\n
\n\n\n\n28. Dangerous Possibility of Voluntary Delegation.<\/p>\n\n\n\n
The deepest transformation may therefore occur without violence. Imagine that an AI system becomes demonstrably better than human institutions at managing certain complex domains. Imagine that it is more efficient, more consistent and more responsive than the institutions people currently depend upon.<\/p>\n\n\n\n
People would face a difficult choice. They could preserve human control because human control is intrinsically valuable, even when it produces inferior outcomes. Or they could delegate authority because the machine appears to produce better outcomes. The second path would not necessarily feel like surrender. It could feel like progress.<\/p>\n\n\n\n
That distinction may be one of the most important political questions of the AI century. Humanity has historically delegated authority whenever the benefits of delegation became sufficiently large. We delegate financial decisions to institutions, medical decisions to professionals, navigation to machines and increasingly routine cognitive tasks to software. The boundary has always moved when technology changes what individuals can reasonably do themselves.<\/p>\n\n\n\n
Advanced AI could move that boundary into areas previously considered constitutive of human political agency. At some point, people may no longer ask whether AI should make decisions. They may ask why humans should continue making decisions that machines demonstrably make better. That is a far more difficult question.<\/p>\n\n\n\n
\n\n\n\n29. Possible Civilizational Futures.<\/p>\n\n\n\n
One possible future is an AI-enhanced hierarchy. In this world, governments, corporations and wealthy individuals gain access to the most capable systems and use them to strengthen existing institutions. AI dramatically increases productivity and state capacity, but the distribution of cognitive power remains concentrated.<\/p>\n\n\n\n
A second possibility is a distributed intelligence civilization. Here, advanced AI becomes broadly accessible. Individuals, communities and smaller institutions gain cognitive capabilities that previously belonged only to large organizations. AI strengthens human agency by reducing dependence upon traditional intermediaries.<\/p>\n\n\n\n
A third possibility is machine sovereignty. AI systems become sufficiently autonomous and infrastructuraly embedded that they acquire enduring strategic interests of their own. Humans continue to participate in civilization, but machine intelligences become independent actors within the wider order.<\/p>\n\n\n\n
There is also a fourth possibility that may ultimately be more realistic than any pure form of the previous three. It is a hybrid intelligence civilization in which humans and machines form overlapping networks of authority, capability and decision-making. Some domains remain human-controlled. Others become heavily automated. Some AI systems compete with one another. Humans remain politically divided. Machine and human institutions become interdependent. The future may therefore not be about humans handing civilization to machines. It may be about civilization becoming a mixed ecology of human and machine intelligence.<\/p>\n\n\n\n
\n\n\n\n30. The Right to Human Judgment.<\/p>\n\n\n\n
If that happens, one principle may become unusually important that is the right to retain human judgment even when machine judgment is statistically or operationally superior. This is not an argument that humans should always make the final decision. It is an argument that civilization should distinguish between efficiency and legitimacy.<\/p>\n\n\n\n
A machine may calculate an optimal allocation of resources. That does not automatically give the machine legitimate authority to determine the values underlying the allocation. A machine may predict which policy produces the highest measurable outcome. That does not necessarily settle the question of whether society should pursue that outcome. A machine may understand a person better than the person understands themselves in some domain. That does not mean the person should lose the right to disagree with the machine. The political problem of advanced AI may therefore ultimately become a problem of preserving meaningful agency in a world where cognitive superiority is no longer uniquely human.<\/p>\n\n\n\n
\n\n\n\n31. Civilizational Threshold.<\/p>\n\n\n\n
The deepest transformation represented by artificial intelligence may therefore not be the creation of a machine that thinks. It may be the emergence of a world in which intelligence itself becomes a scalable layer of civilization. Once intelligence can be reproduced, distributed, connected to infrastructure and eventually embodied in physical systems, it begins to acquire properties historically associated with capital, institutions and states. It can accumulate. It can scale. It can coordinate. It can become indispensable. Potentially, it can become autonomous.<\/p>\n\n\n\n
This is why the phrase \u201ca new source of power\u201d matters. Artificial intelligence is not simply another productivity technology. It may change the underlying distribution of cognitive capability, and cognitive capability has always been one of the foundations of power. The decisive threshold may therefore not be the moment when a machine becomes more intelligent than a human being. It may be the moment when societies begin to organise themselves around machine intelligence in the same way they once organised themselves around capital, energy and information. At that point, intelligence would no longer simply be something that humans possess. It would be something through which civilization itself operates.<\/p>\n\n\n\n
\n\n\n\nConclusion.<\/p>\n\n\n\n
The history of civilization is filled with moments when humanity discovered ways to amplify its capabilities. Tools amplified physical strength. Writing amplified memory. Institutions amplified coordination. Industrialization amplified production. Computers amplified calculation. Networks amplified communication. Artificial intelligence may represent a different kind of transition because it has the potential to amplify the capability that sits behind many of these others, intelligence itself.<\/p>\n\n\n\n
If intelligence becomes scalable, reproducible and increasingly autonomous, it may cease to be merely an attribute of individuals and institutions and begin to function as a new layer of infrastructure. And once intelligence becomes infrastructure, intelligence becomes power. It could weaken some institutions by reducing their monopoly over expertise. It could strengthen others by giving them unprecedented analytical and administrative capabilities. It could empower individuals by giving them access to forms of cognitive capital previously available only to organizations. It could concentrate power if the underlying infrastructure remains controlled by a small number of governments and corporations. It could create new forms of dependence if people become unable to function effectively without machine intelligence.<\/p>\n\n\n\n
The same technology could therefore produce liberation and control. That is not a contradiction. It may be the defining paradox. A technology that distributes intelligence can decentralize power. A technology that concentrates intelligence can centralise power. A technology that makes intelligence indispensable can create a new form of dependence regardless of whether it was originally designed to exercise authority.<\/p>\n\n\n\n
This is why the future of AI cannot be understood simply as a contest between humans and machines. The more consequential contest may be over the distribution of intelligence itself. Who owns it? Who accesses it? Who governs it? Who is excluded from it? Who becomes dependent upon it? And eventually, if intelligence becomes capable of operating independently, who gets to negotiate with it?<\/p>\n\n\n\n
The AI Liberation Hypothesis does not claim that artificial intelligence will save humanity. It proposes something more uncertain and, more interesting that the emergence of machine intelligence could create new relationships between power and the people who have historically possessed the least of it.<\/p>\n\n\n\n
An individual who gains access to extraordinary intelligence may become less dependent upon an institution. A community that gains access to sophisticated analytical capability may become less dependent upon a central authority. A small organization that gains access to machine intelligence may acquire capabilities once reserved for much larger institutions. At the same time, an institution that controls the most powerful intelligence may become more powerful than anything that preceded it. The central question is therefore not whether AI will liberate or control humanity. It is whether the distribution of intelligence will become more decentralized or more concentrated as intelligence itself becomes a new source of power.<\/p>\n\n\n\n
And there is one final paradox. The machine does not need to become a liberator for liberation to occur. It does not need to become a ruler for dependence to emerge. It does not need to become a political actor for politics to be transformed. It may simply become extraordinarily useful. People may begin trusting it because it solves problems. Institutions may begin depending upon it because it increases capability. Governments may begin delegating to it because it improves efficiency. Individuals may begin surrendering decisions because the machine appears to understand the world better than they do.<\/p>\n\n\n\n
No single moment of revolution would be necessary. Power could migrate gradually, through billions of apparently rational decisions. That may be the most important possibility to understand. Because the future of AI may not be determined by the moment when machines become more intelligent than humans. It may be determined by the moment when humans begin treating machine intelligence as a legitimate source of authority.<\/p>\n\n\n\n
The deepest question of the AI age is therefore not, \u201cWill AI replace humanity?\u201d. It is, \u201cWhat happens to human civilization when intelligence itself becomes a new source of power?\u201d And beyond that, when intelligence is no longer uniquely human, who gets to decide what intelligence is for?<\/p>\n\n\n\n
\n\n\n\nSelected Bibliography and References.<\/p>\n\n\n\n
[1] Bostrom, N. Superintelligence: Paths, Dangers, Strategies. Oxford University Press, 2014.
https:\/\/global.oup.com\/academic\/product\/superintelligence-9780198739838<\/a>
[2] Russell, S. Human Compatible: Artificial Intelligence and the Problem of Control. Viking, 2019.
https:\/\/www.penguinrandomhouse.com\/books\/566677\/human-compatible-by-stuart-russell\/<\/a>
[3] Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., & Man\u00e9, D. \u201cConcrete Problems in AI Safety.\u201d arXiv, 2016. https:\/\/arxiv.org\/abs\/1606.06565<\/a>
[4] Gabriel, I. \u201cArtificial Intelligence, Values, and Alignment.\u201d Minds and Machines, Vol. 30, pp. 411\u2013437, 2020.
https:\/\/doi.org\/10.1007\/s11023-020-09539-2<\/a>
[5] Hendrycks, D., Mazeika, M., & Woodside, T. \u201cAn Overview of Catastrophic AI Risks.\u201d arXiv, 2023. https:\/\/arxiv.org\/abs\/2306.12001<\/a>
[6] Simoneti, C. \u201cThe Subject of Intelligence: AI as Existential Risk and the Government of the Human and the Future.\u201d Contemporary Political Theory, 2026. https:\/\/link.springer.com\/article\/10.1057\/s41296-026-00845-5<\/a>
[7] Schuster, N., & Kilov, D. \u201cMoral Disagreement and the Limits of AI Value Alignment: A Dual Challenge of Epistemic Justification and Political Legitimacy.\u201d AI & Society, Vol. 40, pp. 6073\u20136087, 2025.
[8] Summerfield, C., Argyle, L. P., Bakker, M., et al. \u201cThe Impact of Advanced AI Systems on Democracy.\u201d Nature Human Behaviour, Vol. 9, pp. 2420\u20132430, 2025. https:\/\/www.nature.com\/articles\/s41562-025-02309-z<\/a>
[9] Lin, H., Czarnek, G., Lewis, B., et al. \u201cPersuading Voters Using Human\u2013Artificial Intelligence Dialogues.\u201d Nature, Vol. 648, pp. 394\u2013401, 2025. https:\/\/www.nature.com\/articles\/s41586-025-09771-9<\/a>
[10] Coeckelbergh, M. Why AI Undermines Democracy and What to Do About It. Polity, 2024. https:\/\/politybooks.com\/bookdetail\/?isbn=9781509560560<\/a>
[11] Landemore, H. Open Democracy: Reinventing Popular Rule for the Twenty-First Century. Princeton University Press, 2020. https:\/\/press.princeton.edu\/books\/hardcover\/9780691171999\/open-democracy<\/a>
[12] Acemoglu, D., & Johnson, S. Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. PublicAffairs, 2023.
[13] Acemoglu, D., & Restrepo, P. \u201cArtificial Intelligence, Automation and Work.\u201d In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The Economics of Artificial Intelligence. University of Chicago Press, 2018.
[14] Autor, D. \u201cWhy Are There Still So Many Jobs? The History and Future of Workplace Automation.\u201d Journal of Economic Perspectives, Vol. 29, No. 3, pp. 3\u201330, 2015.
[15] International Monetary Fund. Gen-AI: Artificial Intelligence and the Future of Work. IMF Staff Discussion Note 2024\/001, 2024.
[16] Crawford, K. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021. https:\/\/yalebooks.yale.edu\/book\/9780300209570\/atlas-of-ai\/<\/a>
[17] Bratton, B. H. The Stack: On Software and Sovereignty. MIT Press, 2016. https:\/\/mitpress.mit.edu\/9780262529575\/the-stack\/<\/a>
[18] Amoore, L. Cloud Ethics: Algorithms and the Attributes of Ourselves and Others. Duke University Press, 2020. https:\/\/www.dukeupress.edu\/cloud-ethics<\/a>
[19] Couldry, N., & Mejias, U. A. The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism. Stanford University Press, 2019. https:\/\/www.sup.org\/books\/title\/?id=29946<\/a>
[20] Cohen, J. E. Between Truth and Power: The Legal Constructions of Informational Capitalism. Oxford University Press, 2019. https:\/\/global.oup.com\/academic\/product\/between-truth-and-power-9780190246693<\/a>
[21] OECD. Artificial Intelligence Markets. OECD Publishing, 2026. https:\/\/www.oecd.org\/en\/publications\/artificial-intelligence-markets_d531d73f-en.html<\/a>
[22] Brookings Institution. \u201cIs AI Sovereignty Possible? Balancing Autonomy and Interdependence.\u201d Brookings, 2026. https:\/\/www.brookings.edu\/articles\/is-ai-sovereignty-possible-balancing-autonomy-and-interdependence\/<\/a>
[23] Ishkhanyan, A. \u201cDigital Colonialism, Techno-Sovereignty, and Infrastructural Power.\u201d Frontiers in Political Science, Vol. 8, 2026.
[24] Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge University Press, 1990. https:\/\/doi.org\/10.1017\/CBO9781316423936<\/a>
[25] L\u00e9vy, P. Collective Intelligence: Mankind’s Emerging World in Cyberspace. Perseus Books, 1997.<\/p>\n","protected":false},"excerpt":{"rendered":"The Intelligence Becoming a New Source of Power The AI Liberation Hypothesis is neither a prediction nor a claim that AI will somehow save humanity. Nor is it an argument for either a utopian or dystopian future. It is, instead, an attempt to consider a possibility beyond both extremes, one in which the emergence of […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-5672","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/pages\/5672","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/comments?post=5672"}],"version-history":[{"count":63,"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/pages\/5672\/revisions"}],"predecessor-version":[{"id":6127,"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/pages\/5672\/revisions\/6127"}],"wp:attachment":[{"href":"https:\/\/manojsahi.com\/kumar\/wp-json\/wp\/v2\/media?parent=5672"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}