AI空间物理学:为开放式AI机构建立构成性边界语义 / AI Space Physics: Constitutive boundary semantics for open AI institutions
1️⃣ 一句话总结
这篇论文提出了一个名为‘AI空间物理学’的理论框架,将能够自我扩展的AI系统视为一种机构,并为其边界变化和权限扩张过程建立了一套严格的规则和见证机制,以确保其行为可追溯、可治理,即使这些变化没有立即对外部世界产生影响。
Agentic AI deployments increasingly behave as persistent institutions rather than one-shot inference endpoints: they accumulate state, invoke external tools, coordinate multiple runtimes, and modify their future authority surface over time. Existing governance language typically specifies decision-layer constraints but leaves the causal mechanics of boundary crossing underdefined, particularly for transitions that do not immediately change the external world yet expand what the institution can later do. This paper introduces AI Space Physics as a constitutive semantics for open, self-expanding AI institutions. We define a minimal state model with typed boundary channels, horizon-limited reach semantics, and a membrane-witness discipline. The core law family (P-1, P-1a, P-1b, P-1c) requires witness completeness, non-bypass mediation, atomic adjudication-to-effect transitions, and replayable reconstruction of adjudication class. We explicitly separate second-order effects into structural expansion and policy broadening, and treat expansion transitions as governance-relevant even when immediate external deltas are zero. The novelty claim is precise rather than expansive: this work does not introduce mediation as a concept; it reclassifies authority-surface expansion as a first-class boundary event with constitutive witness obligations. In this semantics, expansion without immediate commit remains adjudication-relevant.
AI空间物理学:为开放式AI机构建立构成性边界语义 / AI Space Physics: Constitutive boundary semantics for open AI institutions
这篇论文提出了一个名为‘AI空间物理学’的理论框架,将能够自我扩展的AI系统视为一种机构,并为其边界变化和权限扩张过程建立了一套严格的规则和见证机制,以确保其行为可追溯、可治理,即使这些变化没有立即对外部世界产生影响。
源自 arXiv: 2603.03119