The Dignity-Centric Stack: A Commons-Governed, Horizontally Federated Architecture for Human-Dignity AI

• URL: http://arxiv.org/abs/2606.06083v1
• Date: Thu, 04 Jun 2026 12:21:07 GMT
• Title: The Dignity-Centric Stack: A Commons-Governed, Horizontally Federated Architecture for Human-Dignity AI
• Abstract summary: We argue that a human-dignity-centric digital social contract grounds personal data in human dignity, data personalism, and data sovereignty.<n>We construct a six-layer architecture mapping each dimension onto a layer of commons-governed AI infrastructure.<n>We conclude that commons-governed AI realizes the values the contract proclaims more faithfully than the regulation it presupposes.
• Score: 1.5736899098702974
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The human-dignity-centric digital social contract grounds personal data in human dignity, data personalism, and data sovereignty, and articulates six dimensions of data governance: technological oversight, automation limits, economic justice, political legitimacy, social cohesion, and legal guarantees. It presupposes, however, that enforcement falls to State regulators, licensed fiduciaries, and multi-stakeholder bodies embedded in existing legal systems. This paper asks whether its normative content can instead be realized not as rules imposed on the owners of the AI stack from without, but as a commons-governed infrastructure that any person, firm, or State may use and fund while its governance stays horizontal, polycentric, and subsidiary. We construct the Dignity Stack, a six-layer architecture mapping each dimension onto a layer of commons-governed AI infrastructure, with protocols drawn from the Liberation Stack framework and from the cooperative, mutualist, and libertarian-municipalist traditions. The commons is State-agnostic rather than anti-State, anarchist in its horizontal means but not in the abolition of the State. Its central device is a decoupling of capital from control, by which the stack functions as a shared civic battery, charged by many contributors yet steered by none in proportion to its charge. We prove that this defeats formal capture through votes or surplus, and show that structural capture, the leverage of a dominant supplier free to withdraw what it provides, is resisted only insofar as operational supply is polycentric and substitutable, a condition demanding at the lower layers and perhaps presently unattainable at chip fabrication. We conclude, with explicit attention to its limits, that commons-governed AI realizes the values the contract proclaims more faithfully than the regulation it presupposes.

Related papers

• Governing Well in the Algorithmic Age: The Foundations of Digital Statecraft [1.0188839215540861]
  We argue that 'digital' reconstitutes the statecraft question rather than merely extending its domain.<n>The concept operates on two dimensions - statecraft over digital systems.<n>We derive ten principles of digital statecraft from these foundations.
  arXiv  Detail & Related papers  (2026-07-20T20:01:44Z)
• Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance [1.5736899098702974]
  This article argues that these arrangements form a coherent institutional family, which we call commons-governed artificial intelligence.<n>We contribute a two-dimensional taxonomy whose first axis is the resource layer of the AI stack held in common.<n>We close with the tensions that constrain the project, openwashing, the compute bottleneck, free-riding, and the tension between scale and sustainability.
  arXiv  Detail & Related papers  (2026-06-13T20:53:16Z)
• Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocol [1.5755923640031846]
  We analyze DeAI as a six-layer decentralizing stack.<n>We argue for a shift in the locus of governance from policy to protocol.
  arXiv  Detail & Related papers  (2026-05-23T12:09:56Z)
• Foundation Protocol: A Coordination Layer for Agentic Society [78.01727114524464]
  Foundation Protocol (FP) is a graph-first coordination layer for an emerging human-AI society.<n>FP unifies heterogeneous entities, including agents, tools, resources, humans, institutions, and organizations.<n>The aim is to keep autonomous agency composable while keeping accountability non-negotiable.
  arXiv  Detail & Related papers  (2026-05-22T04:20:35Z)
• AgentCity: Constitutional Governance for Autonomous Agent Economies via Separation of Power [2.173754130697989]
  We term this the Logic Monopoly -- the agent society's unchecked monopoly over the entire logic chain.<n>We propose the Separation of Power (SoP) model, a constitutional governance architecture deployed on public blockchain.<n>In this architecture, smart contracts are the law itself -- the actual legislative output that agents produce and that governs their behavior.
  arXiv  Detail & Related papers  (2026-04-08T12:28:20Z)
• Security, privacy, and agentic AI in a regulatory view: From definitions and distinctions to provisions and reflections [53.468443050795344]
  The rapid proliferation of artificial intelligence (AI) technologies has led to a dynamic regulatory landscape.<n>As AI paradigms shift towards greater autonomy, specifically in the form of agentic AI, it becomes increasingly challenging to articulate regulatory stipulations.<n>This paper reviews the evolving European Union (EU) AI regulatory provisions via analyzing 24 relevant documents published between 2024 and 2025.
  arXiv  Detail & Related papers  (2026-03-19T13:50:52Z)
• The Digital Gorilla: Rebalancing Power in the Age of AI [0.0]
  Article offers a conceptual foundation for AI governance by treating such systems as a fourth societal actor.<n>It develops a Four Societal Actors framework that maps how power flows among these actors across five power modalities.<n>It advances a federalized, polycentric governance architecture and institutionalizes dynamic checks and balances.
  arXiv  Detail & Related papers  (2026-02-23T17:46:54Z)
• Pluralism in AI Governance: Toward Sociotechnical Alignment and Normative Coherence [0.16921396880325779]
  The study synthesises frameworks including Full-Stack Alignment, Thick Models of Value, Value Sensitive Design, and Public Constitutional AI.<n>It introduces a layered framework linking values, mechanisms, and strategies, and maps tensions such as fairness versus efficiency, transparency versus security, and privacy versus equity.<n>The study contributes a holistic, value-sensitive model of AI governance, reframing regulation as a proactive mechanism for embedding public values into sociotechnical systems.
  arXiv  Detail & Related papers  (2026-02-04T14:28:56Z)
• A Technical Policy Blueprint for Trustworthy Decentralized AI [29.298499284846844]
  We propose a Technical Policy Blueprint that encodes governance requirements as policy-as-code objects.<n>We are proposing a Technical Policy Blueprint that separates asset policy verification from asset policy enforcement.
  arXiv  Detail & Related papers  (2025-12-07T21:27:48Z)
• Governable AI: Provable Safety Under Extreme Threat Models [31.36879992618843]
  We propose a Governable AI (GAI) framework that shifts from traditional internal constraints to externally enforced structural compliance.<n>The GAI framework is composed of a simple yet reliable, fully deterministic, powerful, flexible, and general-purpose rule enforcement module (REM); governance rules; and a governable secure super-platform (GSSP) that offers end-to-end protection against compromise or subversion by AI.
  arXiv  Detail & Related papers  (2025-08-28T04:22:59Z)
• Resource Rational Contractualism Should Guide AI Alignment [69.07915246220985]
  Contractualist alignment proposes grounding decisions in agreements that diverse stakeholders would endorse.<n>We propose Resource-Rationalism: a framework where AI systems approximate the agreements rational parties would form.<n>An RRC-aligned agent would not only operate efficiently, but also be equipped to dynamically adapt to and interpret the ever-changing human social world.
  arXiv  Detail & Related papers  (2025-06-20T18:57:13Z)
• Artificial Intelligence in Government: Why People Feel They Lose Control [44.99833362998488]
  The use of Artificial Intelligence in public administration is expanding rapidly.<n>While AI promises greater efficiency and responsiveness, its integration into government functions raises concerns about fairness, transparency, and accountability.<n>This article applies principal-agent theory to AI adoption as a special case of delegation.
  arXiv  Detail & Related papers  (2025-05-02T07:46:41Z)
• AGI, Governments, and Free Societies [0.0]
  We argue that AGI poses distinct risks of pushing societies toward either a 'despotic Leviathan' or an 'absent Leviathan'<n>We analyze how these dynamics could unfold through three key channels.<n> Enhanced state capacity through AGI could enable unprecedented surveillance and control, potentially entrenching authoritarian practices.<n>Conversely, rapid diffusion of AGI capabilities to non-state actors could undermine state legitimacy and governability.
  arXiv  Detail & Related papers  (2025-02-14T03:55:38Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.