Paper 6 — Multi-Layer Cross Verification in the AGI Era: Role Feasibility, Output Reference, and Pre-Transaction Validation

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Authors: The First Waters
Cited by: 52
References: 5

Abstract

This working paper introduces Multi-Layer Cross Verification as a structural methodology for the AGI era. Building on Papers 1 through 5 of the AGI Structural Alignment Series, this paper addresses how AI+AGI outputs may be cross-checked before being associated with roles, responsibilities, authority boundaries, evidentiary references, preservation contexts, or pre-transaction conditions. The framework does not define a fixed fifteen-layer checklist. Instead, the number and composition of verification layers may vary according to output type, domain risk, role sensitivity, authority boundary, transaction relevance, evidentiary requirement, and preservation context. The paper positions role feasibility, output reference, and pre-transaction validation as distinct but related verification-reference domains. It also recognizes that SCD/BIFACE-style coordinates may operate across heterogeneous output units, including document sentences, code functions, image objects, video scenes, subtitles, voice segments, conversation utterances, and revision instructions. This working paper does not present an execution system, payment system, legal determination system, evidentiary-confirmation system, or automated validation engine. It provides a non-executable structural methodology for cross-verifying AI+AGI outputs before they are treated as socially, organizationally, economically, or evidentially relevant. This working paper is Paper 6 of the AGI Structural Alignment Series. This record provides the Expanded Final Publication Edition v3.0 of Paper 6 in the Structural Paper Series under the Research Program on Deterministic Infrastructure and Human-Centered AI Coordination. This version includes unified publication front matter, expanded academic structure, strengthened non-substitution boundaries, and broader cross-domain applicability.

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) AI-based Problem Solving and Planning Digital and Cyber Forensics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
24 May 2026
Language
EN