论文提出 Resourced Authority，用计算预算让治理决定自动执行，比纯靠审批更硬核。
该论文在 arXiv（2608.06353v1）提出名为 Resourced Authority 的机制设计模型，用于对已部署 AI 代理进行持续参与式治理。其核心是把授权与计算资源分配绑定，通过计算预算让治理决定自我执行，并把这套方案定位为部署方之上的合规/共享层。治理周期被建模为序贯到达的验证人类利益相关者参与的扩展式博弈，贡献以独立于代理计算的治理货币计。净支持经资金聚合器转为广度加权有效支持，再由两阈值滞回门变为二元授权，经安全上限耦合映射释放计量计算预算。作者还刻画了该机制可治理的代理类别，并把被治理代理操纵选民国度的挑战列为开放问题。
Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agents
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.