AGI, Governments, and Free Societies

• URL: http://arxiv.org/abs/2503.05710v2
• Date: Thu, 13 Mar 2025 16:15:44 GMT
• Title: AGI, Governments, and Free Societies
• Authors: Justin B. Bullock, Samuel Hammond, Seb Krier,
• Abstract summary: 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper examines how artificial general intelligence (AGI) could fundamentally reshape the delicate balance between state capacity and individual liberty that sustains free societies. Building on Acemoglu and Robinson's 'narrow corridor' framework, we argue that AGI poses distinct risks of pushing societies toward either a 'despotic Leviathan' through enhanced state surveillance and control, or an 'absent Leviathan' through the erosion of state legitimacy relative to AGI-empowered non-state actors. Drawing on public administration theory and recent advances in AI capabilities, we analyze how these dynamics could unfold through three key channels: the automation of discretionary decision-making within agencies, the evolution of bureaucratic structures toward system-level architectures, and the transformation of democratic feedback mechanisms. Our analysis reveals specific failure modes that could destabilize liberal institutions. Enhanced state capacity through AGI could enable unprecedented surveillance and control, potentially entrenching authoritarian practices. Conversely, rapid diffusion of AGI capabilities to non-state actors could undermine state legitimacy and governability. We examine how these risks manifest differently at the micro level of individual bureaucratic decisions, the meso level of organizational structure, and the macro level of democratic processes. To preserve the narrow corridor of liberty, we propose a governance framework emphasizing robust technical safeguards, hybrid institutional designs that maintain meaningful human oversight, and adaptive regulatory mechanisms.

Related papers

• 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)
• A Framework for the Private Governance of Frontier Artificial Intelligence [0.0]
  The paper presents a proposal for the governance of frontier AI systems through a hybrid public-private system. Private bodies, authorized and overseen by government, provide certifications to developers of frontier AI systems on an opt-in basis. In exchange for opting in, frontier AI firms receive protections from tort liability for customer misuse of their models.
  arXiv  Detail & Related papers  (2025-04-15T02:56:26Z)
• Transfeminist AI Governance [0.0]
  Article re-imagines the governance of artificial intelligence (AI) through a transfeminist lens. Building upon trans and feminist theories of ethics, I introduce an approach to transfeminist AI governance.
  arXiv  Detail & Related papers  (2025-03-19T20:25:59Z)
• Media and responsible AI governance: a game-theoretic and LLM analysis [61.132523071109354]
  This paper investigates the interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems.<n>Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes.
  arXiv  Detail & Related papers  (2025-03-12T21:39:38Z)
• AI and the Transformation of Accountability and Discretion in Urban Governance [1.9152655229960793]
  The paper highlights AI's potential to reposition human discretion and reshape specific types of accountability.<n>It advances a framework for responsible AI adoption, ensuring that urban governance remains adaptive, transparent, and aligned with public values.
  arXiv  Detail & Related papers  (2025-02-18T18:11:39Z)
• Decentralized Governance of Autonomous AI Agents [0.0]
  ETHOS is a decentralized governance (DeGov) model leveraging Web3 technologies, including blockchain, smart contracts, and decentralized autonomous organizations (DAOs)<n>It establishes a global registry for AI agents, enabling dynamic risk classification, proportional oversight, and automated compliance monitoring.<n>By integrating philosophical principles of rationality, ethical grounding, and goal alignment, ETHOS aims to create a robust research agenda for promoting trust, transparency, and participatory governance.
  arXiv  Detail & Related papers  (2024-12-22T18:01:49Z)
• Toward Democracy Levels for AI [4.048639768405042]
  We provide a "Democracy Levels" framework for evaluating the degree to which decisions in a given domain are made democratically.<n>The framework can be used (i) to define in a roadmap for the democratic AI, pluralistic AI, and public AI ecosystems, (ii) to guide organizations that need to increase the legitimacy of their decisions on difficult AI governance questions, and (iii) as a rubric by those aiming to evaluate AI organizations and keep them accountable.
  arXiv  Detail & Related papers  (2024-11-14T06:37:45Z)
• 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)
• Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders [59.17981603969404]
  The responsible AI (RAI) community has introduced numerous processes and artifacts to facilitate transparency and support the governance of AI systems. We conduct semi-structured interviews with 19 government, legal, and civil society stakeholders who inform policy and advocacy around responsible AI efforts. We organize these beliefs into four barriers that help explain how RAI artifacts may (inadvertently) reconfigure power relations across civil society, government, and industry.
  arXiv  Detail & Related papers  (2024-08-22T00:14:37Z)
• Managing extreme AI risks amid rapid progress [171.05448842016125]
  We describe risks that include large-scale social harms, malicious uses, and irreversible loss of human control over autonomous AI systems. There is a lack of consensus about how exactly such risks arise, and how to manage them. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems.
  arXiv  Detail & Related papers  (2023-10-26T17:59:06Z)
• Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety [69.59465535312815]
  Regulatory Markets for AI is a proposal designed with adaptability in mind. It involves governments setting outcome-based targets for AI companies to achieve. We warn that it is alarmingly easy to stumble on incentives which would prevent Regulatory Markets from achieving this goal.
  arXiv  Detail & Related papers  (2023-03-06T14:42:05Z)
• Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation [61.77881142275982]
  This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them. We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives. We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
  arXiv  Detail & Related papers  (2022-06-08T12:32:08Z)
• Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance [0.0]
  We present an AI governance framework, which targets organizations that develop and use AI systems. The framework is designed to help organizations deploying AI systems translate ethical AI principles into practice.
  arXiv  Detail & Related papers  (2022-06-01T08:55:27Z)

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.