Reclaiming Constitutional Authority of Algorithmic Power

• URL: http://arxiv.org/abs/2508.11699v1
• Date: Tue, 12 Aug 2025 23:46:30 GMT
• Title: Reclaiming Constitutional Authority of Algorithmic Power
• Authors: Yiyang Mei, Michael J Broyde,
• Abstract summary: Whether and how to govern AI is no longer a question of technical regulation.<n>This Article reconstructs a constitutional framework grounded in covenantal authority and the right of lawful resistance.<n>Individuals retain a constitutional right to resist systems that impose orthodoxy or erode the domain of conscience.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Whether and how to govern AI is no longer a question of technical regulation. It is a question of constitutional authority. Across jurisdictions, algorithmic systems now perform functions once reserved to public institutions: allocating welfare, determining legal status, mediating access to housing, employment, and healthcare. These are not merely administrative operations. They are acts of rule. Yet the dominant models of AI governance fail to confront this reality. The European approach centers on rights-based oversight, presenting its regulatory framework as a principled defense of human dignity. The American model relies on decentralized experimentation, treating fragmentation as a proxy for democratic legitimacy. Both, in different ways, evade the structural question: who authorizes algorithmic power, through what institutions, and on what terms. This Article offers an alternative. Drawing from early modern Reformed political thought, it reconstructs a constitutional framework grounded in covenantal authority and the right of lawful resistance. It argues that algorithmic governance must rest on three principles. First, that all public power must be lawfully delegated through participatory authorization. Second, that authority must be structured across representative communities with the standing to consent, contest, or refuse. Third, that individuals retain a constitutional right to resist systems that impose orthodoxy or erode the domain of conscience. These principles are then operationalized through doctrinal analysis of federalism, nondelegation, compelled speech, and structural accountability. On this view, the legitimacy of algorithmic governance turns not on procedural safeguards or policy design, but on whether it reflects a constitutional order in which power is authorized by the governed, constrained by law, and answerable to those it affects.

Related papers

• 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)
• A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty [35.478378726992]
  We present a structured three-level framework grounded in philosophical uncertainty.<n>We establish five factual determinations about AI consciousness alongside human-centralism as our meta-ethical stance.<n>Our approach balances philosophical rigor with practical guidance, distinguishes consciousness from anthropomorphism, and creates pathways for responsible evolution.
  arXiv  Detail & Related papers  (2025-12-02T09:15:01Z)
• Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance [211.5823259429128]
  We propose a comprehensive framework integrating technical and societal dimensions, structured around three interconnected pillars: Intrinsic Security, Derivative Security, and Social Ethics.<n>We identify three core challenges: (1) the generalization gap, where defenses fail against evolving threats; (2) inadequate evaluation protocols that overlook real-world risks; and (3) fragmented regulations leading to inconsistent oversight.<n>Our framework offers actionable guidance for researchers, engineers, and policymakers to develop AI systems that are not only robust and secure but also ethically aligned and publicly trustworthy.
  arXiv  Detail & Related papers  (2025-08-12T09:42:56Z)
• Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt [44.522343543870804]
  We are worried that such systems, which overlook enduring moral diversity, will spark resistance, erode trust, and destabilize our institutions.<n>This paper traces the underlying problem to an often-unstated Axiom of Rational Convergence: the idea that under ideal conditions, rational agents will converge in the limit of conversation on a single ethics.<n>Treating that premise as both optional and doubtful, we propose what we call the appropriateness framework: an alternative approach grounded in conflict theory, cultural evolution, multi-agent systems, and institutional economics.
  arXiv  Detail & Related papers  (2025-05-08T12:55:07Z)
• 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)
• The Illusory Normativity of Rights-Based AI Regulation [0.0]
  We argue that the rights-based narrative surrounding EU AI regulation mischaracterizes the logic of its institutional design.<n>Our aim is not to endorse the American model but to reject the presumption that the EU approach reflects a normative ideal.
  arXiv  Detail & Related papers  (2025-02-27T03:05:32Z)
• The Fundamental Rights Impact Assessment (FRIA) in the AI Act: Roots, legal obligations and key elements for a model template [55.2480439325792]
  Article aims to fill existing gaps in the theoretical and methodological elaboration of the Fundamental Rights Impact Assessment (FRIA)<n>This article outlines the main building blocks of a model template for the FRIA.<n>It can serve as a blueprint for other national and international regulatory initiatives to ensure that AI is fully consistent with human rights.
  arXiv  Detail & Related papers  (2024-11-07T11:55:55Z)
• Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks [55.2480439325792]
  This paper critically examines the European Union's Artificial Intelligence Act (EU AI Act) Uses insights from Alignment Theory (AT) research, which focuses on the potential pitfalls of technical alignment in Artificial Intelligence. As we apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
  arXiv  Detail & Related papers  (2024-10-10T17:38:38Z)
• Public Constitutional AI [0.0]
  We are increasingly subjected to the power of AI authorities.<n>How can we ensure AI systems have the legitimacy necessary for effective governance?<n>This essay argues that to secure AI legitimacy, we need methods that engage the public in designing and constraining AI systems.
  arXiv  Detail & Related papers  (2024-06-24T15:00:01Z)
• Legitimacy, Authority, and Democratic Duties of Explanation [0.0]
  Secret, complex and inscrutable computational systems are being used to intensify existing power relations. This paper first applies it to opaque computational systems, and clarifies precisely what kinds of explanations are necessary to fulfil democratic values.
  arXiv  Detail & Related papers  (2022-08-18T04:24:28Z)
• The Flaws of Policies Requiring Human Oversight of Government Algorithms [2.741266294612776]
  I propose a shift from human oversight to institutional oversight as the central mechanism for regulating government algorithms. First, agencies must justify that it is appropriate to incorporate an algorithm into decision-making. Second, these justifications must receive democratic public review and approval before the agency can adopt the algorithm.
  arXiv  Detail & Related papers  (2021-09-10T18:58:45Z)

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.