Paper 7 — AGI Output Governance: Candidate Outputs, Human Discretion, and Evidentiary Boundaries in the AGI Era

This working paper introduces AGI Output Governance as a structural framework for positioning AI+AGI outputs as candidate, reference, or assistive outputs before they are mistaken for human judgment, consent, approval, responsibility, evidence, state, execution results, or legal effect. Building on Papers 1 through 6 of the AGI Structural Alignment Series, this paper addresses the positional governance problem of AI+AGI outputs. It defines text, code, image, video, subtitle, voice, prompt, revision, and conversational outputs generated by AI+AGI systems as coordinate-referable candidate, reference, or assistive outputs rather than final states, completed decisions, approvals, evidence, or executable results. The paper does not present a system for controlling AGI itself. It does not perform judgment, approval, consent, evidence confirmation, state generation, execution, settlement, or legal determination. Rather, it provides a non-executable structural framework for keeping AI+AGI outputs below human discretion and within evidentiary, responsibility, and state boundaries. This working paper is Paper 7 of the AGI Structural Alignment Series.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-23
DOI
https://doi.org/10.5281/zenodo.20351229
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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Paper 7 — AGI Output Governance: Candidate Outputs, Human Discretion, and Evidentiary Boundaries in the AGI Era

The First Waters
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Paper 7 — AGI Output Governance: Candidate Outputs, Human Discretion, and Evidentiary Boundaries in the AGI Era

The First Waters
article en

Abstract

This working paper introduces AGI Output Governance as a structural framework for positioning AI+AGI outputs as candidate, reference, or assistive outputs before they are mistaken for human judgment, consent, approval, responsibility, evidence, state, execution results, or legal effect. Building on Papers 1 through 6 of the AGI Structural Alignment Series, this paper addresses the positional governance problem of AI+AGI outputs. It defines text, code, image, video, subtitle, voice, prompt, revision, and conversational outputs generated by AI+AGI systems as coordinate-referable candidate, reference, or assistive outputs rather than final states, completed decisions, approvals, evidence, or executable results. The paper does not present a system for controlling AGI itself. It does not perform judgment, approval, consent, evidence confirmation, state generation, execution, settlement, or legal determination. Rather, it provides a non-executable structural framework for keeping AI+AGI outputs below human discretion and within evidentiary, responsibility, and state boundaries. This working paper is Paper 7 of the AGI Structural Alignment Series.

Zenodo (CERN European Organization for Nuclear Research)
Building Research Institute (JP)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Ethics and Social Impacts of AI
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