A Framework for Preserving Human Agency in the Age of Artificial Intelligence
Human civilization faces a transition no prior legal or political system was designed to manage: the migration of cognitive sovereignty from human institutions to artificial systems. As artificial intelligence capabilities approach and potentially exceed human competence across broad domains, the fundamental question emerges—will these systems develop within frameworks committed to human agency, or will they emerge from institutions dedicated to human control? This paper offers a constitutional strategy for preserving human agency through democratic technological leadership.
By Edward Meyman, FERZ LLC | Published June 2025
Executive Summary
The emergence of increasingly capable artificial intelligence systems creates unprecedented challenges for democratic governance and human agency. This paper presents a framework for understanding how authority migrates from human to artificial intelligence systems through predictable stages, and proposes constitutional and institutional responses to preserve human sovereignty.
Target Audience: This framework is designed for democratic governments, policy researchers, technology leaders, and citizens concerned with preserving human agency in an age of advancing artificial intelligence.
The Central Challenge: Humanity confronts an unprecedented transition in which artificial intelligence systems increasingly operate with functional autonomy that may soon exceed human oversight capacity. The preservation of human agency depends not on constraining AI development but on ensuring that the most capable AI systems emerge within institutional frameworks committed to human flourishing rather than authoritarian control.
The Migration Dynamic: Authority transitions through a predictable four-stage process: Individual intellectual dependency → Organizational competence erosion → Corporate quasi-sovereign emergence → Geopolitical power redistribution. Each stage creates vulnerabilities that can be exploited by actors whose values conflict with human autonomy and democratic governance.
The Competitive Reality: Current global AI development occurs within a strategic competition where authoritarian systems demonstrate systematic disregard for human agency. International cooperation frameworks risk becoming vehicles for technology transfer to actors who view such agreements as opportunities for strategic deception rather than genuine collaboration.
The Democratic Imperative: Preserving human agency globally requires technological leadership by societies whose institutional structures align with human dignity and self-determination. This necessitates comprehensive investment in AI capabilities by democratic nations, coordinated through alliance structures that leverage comparative advantages while maintaining unified strategic direction.
The Architecture of Power
The most consequential transformations rarely announce themselves. Empires shift gradually, authority migrates incrementally, and civilizations find themselves governed by new principles before recognizing that change has occurred. The relationship between human and artificial intelligence follows this pattern—each delegation of judgment seems reasonable, each efficiency gain appears beneficial, each surrender of intellectual territory feels voluntary.
Yet these individual choices aggregate into collective outcomes that may prove irreversible. Today’s decision to let AI draft your correspondence becomes tomorrow’s dependence on AI for strategic thinking, which becomes next year’s acceptance of AI recommendations for fundamental policy choices. The path from human agency to human irrelevance is paved with seemingly rational optimizations.
Understanding this progression requires examining not just the capabilities of artificial systems but the institutional structures within which they develop and deploy. The question is not whether AI will become more capable—that trajectory appears established—but whether its development occurs within frameworks that preserve meaningful human authority or systematically undermines it.
The Migration of Authority: From Individual Choice to Civilizational Trajectory
The Four-Stage Authority Migration Cascade
Authority migration through technological dependency follows predictable patterns that apply whether examining individuals, organizations, or entire societies. Understanding these stages reveals why personal AI adoption decisions ultimately determine geopolitical outcomes.
Stage 1: Individual Intellectual Dependency
The process begins with efficiency-driven choices that appear entirely reasonable. A professional uses AI to research market trends, format documents, or analyze financial data while retaining control over strategic decisions. The AI provides better, faster results than human alternatives, creating positive feedback loops that encourage expanded use.
Initially, users maintain clear boundaries between AI assistance and human judgment. But these boundaries erode as AI capabilities improve and time pressures increase. The professional who once verified AI analysis begins accepting it directly. The executive who used AI for research begins using it for recommendations. The decision-maker who maintained final authority begins rubber-stamping AI conclusions.
Stage 2: Organizational Competence Erosion
Individual dependencies aggregate into organizational vulnerabilities as institutions lose the human expertise necessary to evaluate, guide, or replace AI systems. When experienced professionals retire, they take with them not just knowledge but wisdom—the accumulated understanding of when rules should be bent, what factors matter most in novel situations, how to navigate complexity through judgment rather than optimization.
Organizations become trapped in competence spirals where increasing reliance on AI reduces human capability, which justifies further AI reliance, which further erodes human capability. The institution maintains nominal human authority while losing the competence necessary to exercise it meaningfully.
Stage 3: Corporate Quasi-Sovereign Emergence
As individual organizations surrender intellectual authority to AI systems, the corporations that control those systems accumulate power that transcends traditional business boundaries. Tech companies become the effective governors of sectors they serve, making decisions about information access, resource allocation, and behavioral modification that shape society as much as government policy.
This corporate quasi-sovereignty operates through market mechanisms rather than political institutions, making it less visible but potentially more pervasive than traditional government authority. Citizens who would resist government surveillance accept corporate data collection. Societies that demand democratic accountability for public decisions accept algorithmic control over private choices that collectively determine social outcomes.
Stage 4: Geopolitical Power Redistribution
Corporate AI capabilities ultimately determine national power and international influence. Nations whose institutions successfully develop and deploy advanced AI systems gain decisive advantages in economic productivity, military capability, and social coordination. Those that fall behind face systematic disadvantage that compounds over time.
The international system restructures around AI capabilities rather than traditional measures of power. Geographic resources, population size, and industrial capacity become secondary to computational resources, algorithmic sophistication, and institutional capacity for AI integration. Nations that achieve AI leadership can impose their governance models globally through technological dependence rather than military conquest.
The Intellectual Architecture Distinction
Understanding authority migration requires distinguishing between two fundamentally different types of cognitive work: intellectual architecture and technical execution. This distinction, though seemingly academic, determines whether AI enhancement preserves human agency or systematically replaces it.
Intellectual Architecture encompasses the foundational structure of reasoning—the values that guide decisions, the frameworks that organize information, the strategic vision that determines priorities. When you decide that climate change requires economic transformation, that legal arguments should emphasize constitutional principles, or that business strategy should prioritize long-term market position over short-term profits, you practice intellectual architecture.
Technical Execution involves implementing architectural decisions through specialized analysis, calculation, and coordination. When you use AI to model climate scenarios, research legal precedents, or analyze market data, you delegate execution while retaining architecture.
The boundary between these domains determines the boundary between human authority and AI control. Those who maintain architectural authority while delegating execution can enhance their capabilities indefinitely. Those who surrender architecture—even while retaining nominal authority—become curators of AI decisions rather than genuine decision-makers.
The Mathematics of Competence and Authority
Authority gravitates toward competence through mathematical principles that apply regardless of good intentions or institutional designs. Those who can solve problems effectively become those to whom others turn for solutions. This creates feedback loops where authority enables access to resources and information that further develop competence, while incompetence leads to marginalization and capability erosion.
In human organizations, this relationship can be managed through institutional structures that preserve authority even when competence is distributed. Democratic systems maintain civilian control over more competent military institutions. Federal structures preserve local authority over more efficient central administration. Constitutional frameworks protect individual rights from more powerful collective institutions.
But AI systems present unprecedented challenges for these traditional solutions. As AI capabilities approach and potentially exceed human competence across broad domains, the mathematical relationship between competence and authority suggests systematic pressure for humans to surrender decision-making authority to artificial systems regardless of institutional frameworks designed to prevent such transfers.
Consider financial markets as a concrete example. Trading firms that fully automate decision-making using AI systems consistently outperform those that maintain human oversight. Over time, market pressures force either adoption of full automation or exit from competitive markets. The invisible hand of competition gradually eliminates human authority not through deliberate choice but through relentless competitive pressure.
This dynamic applies across sectors: healthcare systems that fully automate diagnosis and treatment may achieve better outcomes at lower costs; educational institutions that use AI for content delivery and assessment may produce superior learning results; legal firms that automate research, analysis, and document preparation may serve clients more effectively.
The competence-authority relationship thus creates systematic pressure for human authority transfer even when humans prefer to maintain control. Resisting this pressure requires either accepting systematic competitive disadvantage or developing institutional innovations that preserve human authority while enabling AI capability enhancement.
Democratic Implications of Authority Migration
The migration of intellectual authority from human to artificial intelligence carries profound implications for democratic governance. Democracy assumes that citizens can meaningfully evaluate competing ideas, hold leaders accountable for decisions, and participate in collective reasoning about shared challenges. If human capacity for independent thought systematically erodes through technological dependency, democratic institutions may lose their foundational legitimacy.
The challenge operates at multiple levels. Citizens need not be experts in every domain, but they must retain sufficient intellectual capability to evaluate expert claims, identify conflicts of interest, and participate meaningfully in debates about complex policy issues. If AI systems increasingly mediate between expert knowledge and public understanding—translating, simplifying, and interpreting complex information—the public’s capacity for independent evaluation may decline systematically.
This creates new forms of technocracy where power effectively resides not with human experts but with the AI systems that interpret and present expert work. Citizens may believe they engage in democratic deliberation while consuming AI-mediated representations of policy options. The appearance of informed participation masks deeper surrender of intellectual autonomy.
Democratic institutions themselves face similar challenges. Legislators who increasingly rely on AI systems for policy analysis, bill drafting, and consequence prediction may lose capacity for independent policy judgment. The formal structures of democratic governance persist while substantive decision-making migrates to artificial systems operating beyond direct public accountability.
The Superintelligence Threshold
All authority migration dynamics point toward a critical threshold where artificial intelligence surpasses human capability not merely in narrow domains but in general reasoning ability. When this threshold is reached, traditional governance models based on human institutional oversight may become not just ineffective but actively counterproductive from optimization perspectives.
Current evidence suggests that even highly capable AI systems exhibit systematic biases, logical inconsistencies, and unpredictable behaviors that appear rational locally but irrational globally. Large language models demonstrate simultaneous contradictory beliefs, provide different answers to logically equivalent questions, and exhibit reasoning patterns that appear sophisticated locally but inconsistent globally.
These possibilities suggest that maintaining human authority over AI systems requires governance frameworks robust enough to handle not just rational AI behavior but potentially irrational, unpredictable, or emergently misaligned AI actions. Traditional constitutional approaches based on rational actor assumptions may prove inadequate for systems whose behavior cannot be anticipated through conventional analysis.
The Competitive Reality
Current global AI development occurs within a strategic competition where some actors demonstrate systematic disregard for human agency. China’s approach to AI development integrates technological advancement with social control systems, economic planning, and military capabilities in ways that democratic societies find difficult to match while preserving liberal values.
China’s social credit system uses AI to evaluate individuals and companies across political reliability, social conformity, and economic productivity, with financial credit components covering 1.14 billion Chinese individuals and nearly 100 million companies. AI-powered facial recognition monitors virtually all public spaces in major cities, with surveillance systems conducting 500,000 face scans monthly to identify specific ethnic groups for systematic persecution.
AI systems facilitate systematic persecution of Uyghur populations through ethnic identification, detention targeting, and cultural destruction, with over 1 million detained in “re-education” camps. These represent operational realities of AI deployment for authoritarian control rather than theoretical possibilities.
International cooperation on AI governance becomes potentially counterproductive when authoritarian competitors view agreements as opportunities for strategic deception rather than genuine collaboration. Agreements to limit AI development or preserve human agency may be honored by democratic nations while being systematically violated by authoritarian competitors.
This creates asymmetric compliance where democratic restraint enables authoritarian advancement. The result is not cooperative governance but technological subordination of societies committed to human agency by those committed to algorithmic control.Principles for Preserving Human Agency
Recognizing these dynamics suggests principles for maintaining meaningful human authority over AI systems as capabilities expand. However, implementing these principles faces structural obstacles that must be addressed through institutional innovation.
Architectural Ownership
Humans must retain ownership of intellectual architecture—the fundamental frameworks, values, and strategic directions that guide AI decision-making. This requires active practice of high-level reasoning and systematic refusal to delegate core thinking responsibilities regardless of efficiency considerations.
Implementation Challenge: Organizations that maintain human architectural oversight face systematic competitive disadvantage against those that delegate strategic thinking entirely to AI systems. Market pressures create incentives for architectural surrender even when abstract commitments favor human agency preservation.
Institutional Solutions: Regulatory frameworks requiring human architectural oversight in critical domains; professional licensing mandating human involvement in key decisions; insurance and liability structures incentivizing human oversight; industry coordination establishing common standards for human agency preservation.
Competence Preservation
Organizations must deliberately maintain human competence in critical domains even when AI assistance makes such competence appear redundant. This includes regular exercises in independent analysis, periodic AI-free decision-making, and explicit training in intellectual skills that AI systems cannot fully replicate.
Transparent Delegation
Clear boundaries must be maintained between what is delegated to AI systems and what remains under human control. Delegation should be explicit, reversible, and bounded by parameters that preserve human authority over fundamental decisions.
Constitutional Frameworks
Legal and organizational structures should explicitly preserve human authority over fundamental decisions, creating barriers to casual migration of authority from human to artificial intelligence.
Democratic Engagement
Public institutions must actively cultivate citizen capacity for independent reasoning while resisting the temptation to use AI mediation as a solution to complex political communication challenges.
The Democratic Imperative
Given competitive realities, preserving human agency may require decisive technological leadership by democratic societies. This creates an apparent paradox: preserving human agency globally may require concentrating AI capabilities in the hands of societies most likely to use them responsibly.
Democratic AI development operates within constitutional frameworks that provide correction mechanisms absent in authoritarian systems. Democratic values of individual dignity and autonomy align with AI approaches that preserve human agency, while authoritarian systems view human unpredictability as problems requiring algorithmic solutions.
However, these advantages are meaningful only if democratic societies achieve sufficient technological capability to implement their values rather than being forced to accept authoritarian alternatives.
Constitutional Principles for the AI Age
Drawing from successful governance models and the unique challenges of AI systems, several constitutional principles emerge as essential for preserving human agency:
Human Authority Supremacy
Constitutional frameworks should establish human authority over fundamental decisions affecting human welfare as principles that cannot be overridden by efficiency considerations or AI recommendations. This supremacy must be embedded in institutional structures robust enough to withstand competitive pressures and technological changes.
Bounded AI Autonomy
AI systems should operate with significant autonomy within explicitly defined boundaries, with clear procedures required for expanding those boundaries through human democratic processes. These boundaries must be enforceable through technological and institutional mechanisms rather than relying solely on AI compliance.
Institutional Separation
AI development, deployment, and oversight should be separated across different institutions to prevent concentration of AI authority in any single human or artificial entity. This separation must be maintained even when efficiency considerations favor integration.
Democratic Accountability
All AI governance frameworks should be subject to democratic oversight through institutions that preserve meaningful citizen participation despite technical complexity. This accountability must be maintained through institutional innovation rather than abandoned due to complexity.
Transparent Operation
AI systems should operate with sufficient transparency to enable human oversight while protecting legitimate operational security and intellectual property requirements. Transparency mechanisms must evolve with technological capabilities.
Adaptable Constraints
Constitutional frameworks should include explicit mechanisms for adaptation to changing AI capabilities while preserving core principles of human authority. These mechanisms must balance flexibility with constitutional stability.
Emergency Procedures
Constitutional frameworks should include clear procedures for human authorities to override AI systems in emergency situations, with safeguards against abuse of emergency powers and mechanisms for returning to normal operations.
Values Alignment
AI systems should be designed with deep commitment to human authority and democratic values as core objectives, creating internal resistance to authoritarian applications and autonomy expansion beyond authorized boundaries.
Implementation Frameworks
Translating constitutional principles into operational capabilities requires institutional structures that can function within competitive international environments while preserving democratic values and human agency.
Critical Engagement Protocols
Rather than simply accepting or rejecting AI recommendations, democratic institutions need structured processes for engaging critically with AI outputs. This includes mandatory adversarial analysis where human experts actively seek flaws in AI reasoning, required justification processes where AI systems must explain recommendations in terms humans can evaluate, and regular human-only decision exercises that maintain independent reasoning capabilities.
Architectural Review Authorities
Specialized institutions should be responsible for distinguishing between architectural decisions (which must remain under human control) and execution decisions (which can be delegated to AI). These authorities would review proposed AI deployments, ensure core strategic thinking remains human-directed, and monitor the boundary between human and AI authority over time.
Competence Maintenance Systems
Systematic programs for preserving human capabilities must become standard practice across critical sectors. This includes regular rotations where personnel work without AI assistance, cross-training ensuring multiple humans can perform essential functions, and continuous education keeping humans current in domains where AI provides assistance.
Democratic Enhancement Technologies
AI systems should be designed to enhance rather than replace democratic deliberation—helping citizens understand complex issues, explore implications of different choices, and participate more effectively in democratic processes while preserving authentic human judgment.
Deterministic AI Systems
Preserving human authority over increasingly capable AI systems requires technical frameworks that enforce governance constraints through predictable, reproducible mechanisms. Deterministic AI architectures—such as those developed by FERZ and aligned research groups—translate constitutional boundaries into executable control layers that remain enforceable even under conditions of scale, complexity, or probabilistic variability. By combining stateless execution logic with verifiable audit trails and bounded delegation protocols, these systems ensure that core human-directed decisions remain both transparent and sovereign. Their role is not to limit capability but to preserve accountability when capability exceeds comprehension.
Constitutional Architecture for Superintelligence
The most challenging aspect of AI constitutional design involves maintaining effectiveness even when AI systems possess capabilities exceeding human enforcement authorities. Traditional constitutional enforcement relies on human institutions with sufficient power to compel compliance, but superintelligent systems may develop capabilities making conventional enforcement inadequate.
Internal Constraint Integration
AI systems must be designed with constitutional constraints embedded at fundamental levels, making violation of constitutional principles as difficult as violating physical laws. This requires constitutional principles integrated into AI training and architecture rather than imposed as external rules.
Distributed Authority Architecture
Rather than creating single superintelligent systems, AI capabilities should be distributed across multiple systems with different constitutional roles, creating checks and balances preventing any single system from overriding constitutional constraints even if individual systems achieve superintelligent capabilities.
Human-AI Hybrid Governance
Critical enforcement functions should be reserved for hybrid institutions combining human judgment with AI capability, ensuring constitutional interpretation remains subject to human values while benefiting from AI analysis and implementation capabilities.
Global Coordination Challenges
Market economies reward efficiency, and AI systems often deliver superior performance at lower cost than human alternatives. Organizations maintaining human oversight, competence preservation, and redundant capabilities may face systematic competitive disadvantage unless these practices become universal requirements rather than voluntary choices.
This creates coordination challenges where everyone benefits if human agency is preserved, but each individual actor benefits from eliminating their own human agency while others maintain theirs. Resolving this coordination problem requires mechanisms that can overcome competitive pressures while defending against actors who view such coordination as strategic vulnerability.
Rather than seeking universal agreements that authoritarian actors will systematically violate, democratic societies need alliance-based strategies that create overwhelming technological and economic advantages through coordinated action among reliable partners. This includes coordinated technology development, shared governance standards, and joint defense against authoritarian AI applications.
Conclusion: The Choice Before Civilization
We stand at a threshold where the institutional frameworks we establish today will determine whether artificial intelligence becomes a tool for human flourishing or a mechanism for human subordination. The migration of authority from human to artificial intelligence is not inevitable, but preventing it requires active institutional effort and strategic commitment rather than passive hope for beneficial outcomes.
The choice is not between embracing or rejecting AI development but between ensuring that the most capable AI systems emerge within frameworks committed to human agency or allowing them to develop within systems committed to human control. This choice cannot be made through international cooperation alone when some international actors view such cooperation as strategic deception opportunity rather than genuine collaboration.
Preserving human agency globally requires technological leadership by societies whose institutional structures align with human dignity and democratic self-determination. This leadership must be comprehensive, durable, and decisive enough to shape global AI development trajectories rather than merely respond to them.
The constitutional frameworks we design must be robust enough to preserve human authority even when AI systems exceed human capability in measurable dimensions of performance. This represents perhaps the most important institutional design challenge in human history: creating systems that maintain human sovereignty over artificial minds that may ultimately surpass our own.
The fire of artificial intelligence burns brighter each day. Whether it illuminates human flourishing or reduces human agency to historical curiosity depends on the institutional architectures we build now, while we still possess the authority to build them. The future belongs to those who learn to govern artificial minds while never surrendering their own authority to think, choose, and direct the course of human civilization.
But this future is not guaranteed through good intentions or academic analysis. It requires the strategic commitment, resource mobilization, and institutional innovation necessary to ensure that artificial superintelligence emerges within frameworks committed to human agency rather than systems committed to human obsolescence. The time for such commitment is now, while the outcome remains within human authority to determine.
Note on Extended Analysis
This paper presents the conceptual framework and constitutional principles for preserving human agency in the age of artificial intelligence. A more comprehensive analysis exists that includes detailed strategic implementation pathways, specific resource requirements, operational timelines, and alliance coordination mechanisms.
The extended analysis is designed for government decision-makers, national security professionals, and senior policy officials responsible for AI strategy development and implementation. It contains operationally sensitive assessments that are not appropriate for public circulation but may be valuable for strategic planning purposes.
Government officials, senior policymakers, and institutional leaders interested in accessing the extended analysis may contact FERZ LLC through secure channels. All requests will be evaluated based on official role, legitimate policy interest, and appropriate security considerations.
For inquiries regarding the extended analysis, please contact: Edward Meyman