TGC(Trust Graph Consensus) v2 – Machine-Layer Deterministic Trust Governance Protocol

This paper introduces TGC v2, a deterministic governance protocol that formalizes trust as a machine-verifiable object and models collective decision-making through structured, localized democratic processes. Unlike blockchain systems that treat trust as something to be eliminated (“trustless” computation), TGC conceptualizes trust as a relational and responsibility-bearing structure. The protocol encodes trust into discrete Trust Objects—formal entities with signature, weight, scope, and expiry—thereby transforming trust from a sociological intuition into an ontologically explicit and computationally actionable component. The TGC framework is built on a Root–Sub delegation graph in which all governance occurs strictly at Depth-1, reflecting the philosophical insight that legitimate authority emerges from immediate relational constituencies rather than abstract global majorities. Consensus is resolved through a 51% rule among direct dependents, with abstentions automatically recognized through time-bounded voting windows to guarantee liveness. Structural transitions—joining, merging, detaching—are governed not by coercion but by localized democratic authority and responsibility symmetry. This produces a novel form of computational legitimacy where power and responsibility are structurally inseparable. TGC v2 contributes to political philosophy, social ontology, governance theory, and the philosophy of information by offering the first formal model in which trust, responsibility, and authority are expressed as deterministic state transitions rather than sociological metaphors. It provides a conceptual and computational alternative to traditional blockchain consensus, Liquid Democracy, and DPoS models, none of which capture the structural interplay of relational trust and democratic responsibility embodied in TGC. Finally, the paper outlines how this deterministic trust layer becomes the foundation for TGC v3, a human–AI hybrid governance architecture. In v3, machine-verifiable trust structures (from v2) integrate with human oversight, ethical constraints, and meta-level rule formation. This connection demonstrates how objectified trust can bridge the gap between human governance and algorithmic authority, enabling autonomous systems that remain aligned with democratic principles. Thus, TGC v2 is both a standalone theoretical contribution and the necessary substrate for next-generation AI-integrated governance systems.