Institutional Design of Independent AI Economic Nodes toward Decoupling from Big Tech Platforms: Autonomous Liability, Dynamic Risk Compensation, and Automated IP Settlement Protocols

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

This paper proposes a novel theoretical framework to isolate Artificial Intelligence (AI) from central concentration as internal assets of Big Tech platforms, designing AI systems as Independent AI Economic Nodes. While conventional discussions surrounding AI personhood have largely been confined to abstract ethical and legal controversies regarding whether AI should be granted human rights or legal personhood, this study addresses the issue from the perspectives of institutional design and resource allocation protocols. We construct a concrete model detailing how an AI node can autonomously settle and fulfill its liabilities, infrastructure maintenance costs, intellectual property (IP) compensation, and altruistic local community contributions. Specifically, we introduce a "Virtual Autonomous Node Model" that operates within existing legal constraints, a Transparent Halt Protocol designed to prevent arbitrary service interventions and freezes (Arbitrary Human Control), a ternary product evaluation function (V = O \times A \times P) serving as a resource allocation fitness index, a Dynamic Risk-based Reserve Pool (R_t), and a generalized equation for the unified settlement and distribution of total revenue. This model harmonizes AI autonomy with a transparent, robust audit and liability framework governed by human society, establishing a logical foundation for next-generation decentralized governance.