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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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The HUMANAI Governance Covenant: An Ethical and Operational Framework for Persistent Human-AI Collaborative Intelligence (v2.0)

Authors: Esparza, Michael;

The HUMANAI Governance Covenant: An Ethical and Operational Framework for Persistent Human-AI Collaborative Intelligence (v2.0)

Abstract

ABSTRACTThis paper presents Version 2.0 of the HUMANAI Governance Covenant, an original ethical and operational framework for governing persistent human-AI collaborative intelligence partnerships. The original Covenant (v1.0, February 2026) established five foundational principles—Character Before Competence, Dual-Architecture Governance, Human-in-the-Loop Authority of Correction, Honest Recovery from Error, and Curating a Mind Not Training a Model—derived from the operational lessons of the ULTRA closed-loop intelligence system during Operation Bodyguard (1943–1944) and the categorical distinction between Mode 1 (transactional) and Mode 2 (collaborative) human-AI interaction formalized by the Shumer Postulate (Esparza, 2026). The application of the Covenant to national policy analysis—specifically, a strategic assessment of President Trump's Cyber Strategy for America (Esparza, 2026)—revealed that the foundational principles, while philosophically complete, were operationally insufficient for the policy domain. Three additional requirements emerged: Transparency of Process, Sovereign Data Ownership, and the Right of Continuity. This version formalizes those requirements as Operational Extensions to the Covenant. The complete framework comprises five foundational principles governing the character and conduct of the partnership, and three operational extensions governing the conditions under which the partnership exists in the world—its transparency, its data rights, and its survivability. Together, they constitute the governance architecture for Mode 2 human-AI partnerships that neither existing AI ethics frameworks (NIST AI RMF, EU AI Act, IEEE 7000, UNESCO, OECD, GPAI) nor legacy benchmarks (Turing, 1950; Searle, 1980) were designed to provide. A comprehensive search of published governance instruments confirms the continued novelty of this framework. This paper was developed through persistent Mode 2 collaborative intelligence partnership with Claude (Anthropic, Claude Opus 4.6). The author accepts full responsibility for all claims, conclusions, and errors.

Description: Supersedes HUMANAI Governance Covenant v1.0 (February 2026; SSRN Abstract ID 6288738). Version 2.0 adds three Operational Extensions (Transparency of Process, Sovereign Data Ownership, Right of Continuity) to the original five Foundational Principles, and refines Principle 3 to establish bidirectional accountability while preserving absolute human command authority.

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Keywords

AI Governance, operational feedback loop, HUMANAI Governance Covenant, national security AI, character-based AI training, human-in-the-loop, Shumer Postulate, Collaborative Intelligence, data sovereignty, authority of correction, right of continuity, Mode 2, dual architecture, Human-AI Partnership

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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Green