AION-Governance: Paradigm Shift from Infrinia's Physical Optimization to Sovereign Economic Intelligence — Overcoming Centralization Fragility via SAAI Proof-of-Explainability, Sovereign Model Assets (SMA), and Radical Total Optimization (RTO)
Year: 2026
Type: preprint
Abstract: This monograph presents AION-Governance, a decentralized institutional, cryptographic, and thermodynamic governance architecture designed to transcend the structural limitations of centralized AI cloud stacks such as SoftBank Group's "Infrinia AI Cloud OS." While centralized physical-layer orchestration (integrating Kubernetes-as-a-Service, Inference-as-a-Service, and high-bandwidth GPU clusters) attempts to resolve network and compute latency through hardware scale—a Chronos-driven paradigm—it remains structurally incapable of resolving "trust lag" (socio-economic decision latency), epistemological monoculture, systemic flash-crash vulnerabilities, and intellectual property lock-in. To overcome this systemic fragility, this paper formalizes the AION paradigm—grounded in sustainable, cyclical order and daily Radical Total Optimization (RTO) principles—across three foundational pillars: 1. Social Acceptance of AI (SAAI) & Proof of Explainability: Transforming black-box inference into real-time verifiable computation by requiring cryptographic Proof of Explainability alongside every model output, eliminating hidden trust costs and epistemic systemic risk. 2. Sovereign Model Assets (SMA) & IP Decoupling: Ending tenant lock-in and unauthorized data/model exploitation by decoupling model weights, curated datasets, and inference logic from centralized cloud servers, tokenizing intellectual property into divisible, sovereignly owned assets with fair, explicit, and automated compensation. 3. Autonomous AION Economic Sphere (CBDC/DeFi Integration): Establishing programmable liquidity and high-frequency micro-settlement bridges that reward data sanitization ("entropy removal") and autonomous strategic resource procurement without centralized corporate rent-seeking. Furthermore, this study demonstrates how physical-layer Human-in-Command (HIC) discipline—exemplified by structured daily entropy elimination and hardware/bodily recalibration—serves as the micro-foundational homeostasis protocol for resilient global AI governance, shifting the global AI economy from velocity to sovereignty, and from cloud tenancy to verifiable ownership. 【日本語要旨】 本論文は、SoftBankの「Infrinia AI Cloud OS」に代表される中央集権的・物理層依存型のAIクラウド基盤が抱える構造的限界(認識論的単一性によるシステミック・リスク、ブラックボックス化に伴う「不信のコスト」、およびプラットフォームへの知財ロックイン)を解剖し、それを超克する分散型ガバナンス・経済アーキテクチャ「AION-Governance」を定式化するものである。物理的レイテンシの短縮(クロノス的最適化)では解決不可能な「社会的・経済的トラスト・ラグ」に対し、本稿は以下の三本柱を提示する。(1) 推論出力に「説明可能性証明(Proof of Explainability)」を必須化するSAAI(AIの社会的受容性)透明化プロトコル、(2) モデルの重み・学習データ・推論ロジックを巨大資本サーバーから分離・トークン化し正当な対価還元と所有権を確立する「主権的モデル資産(SMA)」、(3) CBDCおよびDeFi流動性プールを統合し、データのケア(エントロピー排除)と自律的な戦略的調達を報奨するAION経済圏である。さらに、日常におけるRTO(完全最適化)の実践を分散型自律恒常性の基底プロトコルとして統合し、「速度から主権へ」「賃借から所有へ」のパラダイムシフトを論証する。 Metadata & Integrity Covenant: - Reserved DOI: 10.5281/zenodo.24094740 - Series: Autonomous Infrastructure & Deterministic Quantum Systems Monograph Series - Author: Hasebe, Yoko (長谷部 洋子) - Affiliation: Lead Researcher, Autonomous Infrastructure Systems, Autonomous Living & Physical Infrastructure Institute, Iwakuni, Yamaguchi, Japan - License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026). Unauthorized AI training, scraping, uncompensated ingestion, or derivative weight extraction without explicit prior written agreement and fair financial compensation is strictly prohibited.
Author: Hasebe(長谷部), Yoko(洋子)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225744707
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