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

TL;DR

A conceptual working paper presenting a structural governance framework to keep AI+AGI outputs within human discretion and evidentiary boundaries.

Problem

Outputs generated by AI+AGI systems—such as text, code, images, and voice—are often mistaken for human judgment, consent, approval, responsibility, evidence, or execution results. This misidentification must be addressed.

Approach

Define outputs as 'candidate', 'reference', or 'assistive' outputs rather than final states or decisions, and assign coordinate referability to keep them under human discretion through a non-executable structural framework.

Results & Contribution

Provides a conceptual contribution by setting boundaries that limit the legal and liability effects of AGI outputs, but does not include actual implementation or experimental validation.