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Source note2 min read

Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agents

Source

arXiv

arxiv.org/abs/2608.06353v1

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Source

Plain-Language Brief

The authors propose a model for continuous participatory governance of AI agents, focusing on controlling them through resource allocation to make authorization self-enforcing via compute budgets. The model consists of an extensive form game where verified human stakeholders contribute to a governance currency and a funding aggregator converts contributions into a binary authorization that releases metered compute budgets. The paper identifies the manipulation of the governing electorate by the governed agent as the central open problem.

What the Document Says

  • The authors present a mechanism design model for continuous participatory governance of AI agents.
  • The model is based on resource allocation for self-enforcing authorization through compute budgets.
  • The extensive form game includes verified human stakeholders contributing to a governance currency.
  • A funding aggregator converts raw contributions into breadth weighted effective supports.
  • A two threshold gate with hysteresis converts net support into binary authorization.
  • Binary authorization, through a coupling map and an exogenously certified safety ceiling, releases metered compute budgets.
  • The model characterizes the class of agents it can govern.
  • Manipulation of the governing electorate by the governed agent is identified as the central open problem.

Key Concepts Mentioned

  • Participatory Governance
  • AI Agents
  • Resource Allocation
  • Compute Budgets
  • Extensive Form Game
  • Verified Human Stakeholders
  • Governance Currency
  • Funding Aggregator
  • Breadth Weighted Effective Supports
  • Two Threshold Gate with Hysteresis
  • Binary Authorization
  • Coupling Map
  • Safety Ceiling
  • Metered Compute Budgets

Claims Made by the Document

  • The proposed model can govern a certain class of AI agents.
  • Manipulation by the governed agent is a significant problem.

Evidence Used

  • The authors present a detailed mechanism design model in the text.

Methods / Approach

UNKNOWN

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

UNKNOWN

Open Questions

UNKNOWN

Notes for Future Q&A

May include interpretation. Labeled where it does.

UNKNOWN

Raw Abstract / Excerpt

We give a formal mechanism design model for the continuous participatory governance of a deployed AI agent. The mechanism is built on the principle that governance should control an AI agent through resource allocation so as to make authorization self enforcing via compute budgets. The mechanism seeks to establish the Safe AI paradigm that compute is an effective governance lever. We situate our work as a compliance or commons overlay on a deployer. One governance period is an extensive form game in which verified human stakeholders arrive sequentially and contribute, on a provision or a rejection market, in a governance currency that is deliberately distinct from the agents compute. A funding aggregator turns raw contributions into breadth weighted effective supports - a two threshold gate with hysteresis converts net support into a binary authorization that, through a coupling map bounded by an exogenously certified safety ceiling, releases a metered compute budget - realized in hardware as a signed compute license so that the decision is self-enforcing. We characterize the class of agents the mechanism can govern and isolate manipulation of the governing electorate by the governed agent as the central open problem. We also introduce several challenges addressing manipulation of governing electorate by the governed agents.