What question did this study set out to answer?

The study aims to establish a governance framework that ensures AI systems enhance human capabilities without undermining authority.

June 8, 2026Open Access

Vela Protocol: A Governance Framework for Human-Centered AI Infrastructure

Key Points

The study aims to establish a governance framework that ensures AI systems enhance human capabilities without undermining authority.
Identified six structural issues in the digital environment influencing AI deployment.
Proposed six guiding principles to address these issues and uphold human agency.
Detailed the instantiation of the Vela Protocol across various AI systems.
Introduced six principles: Transparency, Accountability, Human Agency, Systems Integrity, Social Resilience, Governance Continuity Under Scale.
Outlined the implementation of the Vela Signing Protocol v1.0 in governed AI environments.
Demonstrated how the framework integrates across systems like PromptLedger, LayerCake, and Aura Collective.

Abstract

This paper presents Vela Protocol, a governance framework for human-centered AI infrastructure built on the principle that AI should amplify human capability without absorbing human authority. It documents six structural fractures in the current digital environment — language erasure, transparency theater, designed exclusion, weaponized information, the privacy lie, and the builder's trap — and presents the six founding principles through which Vela Protocol addresses them: Transparency, Accountability, Human Agency, Systems Integrity, Social Resilience, and Governance Continuity Under Scale. The paper describes the instantiation of the framework across a family of governed AI systems including PromptLedger, LayerCake, Velcro Wallet, and Aura Collective, and presents the Vela Signing Protocol v1.0. Related publication: Stuart-Mueller, L. (2026). VelaHub.dev Related publication: Stuart-Mueller, L. (2026). PromptLedger: AI Governance Infrastructure for Institutional Deployment. Zenodo. DOI: 10.5281/zenodo.20320449 Related publication: Stuart-Mueller, L. (2026). From Semiotic Relationships to Code in the AI Governance Stack. Zenodo. DOI: 10.5281/zenodo.20387854 Related publication: Stuart-Mueller, L. (2026). Cognition Is Not Authority: A Practical Governance Architecture for AI Execution in Regulated Environments. Zenodo. DOI: 10.5281/zenodo.20387945 Related publication: Stuart-Mueller, L. (2026). PromptLedger: A Pre-Execution Governance Architecture for Enterprise AI. Zenodo. DOI: 10.5281/zenodo.20455428 Related publication: Stuart-Mueller, L. (2026). NeuralPulse: An Editorial Governance Framework for Open AI Research Publishing Under Human Authority. Zenodo. DOI: 10.5281/zenodo.20564475 Related publication: Stuart-Mueller, L. (2026). Alignment Is Not Collaboration: On Intellectual Property Standards in the Age of AI. Zenodo. DOI: 10.5281/zenodo.20564847 Related publication: Stuart-Mueller, L. (2026). PromptLedger: A Nine-Layer Pre-Execution Governance Architecture for Enterprise AI Compliance, Auditability, and Human Oversight. Zenodo. DOI: 10.5281/zenodo.20564544 (awaiting confirmation) Related publication: Stuart-Mueller, L. (2026). Governed Creative Generation: A Structured Intent Decomposition Architecture for Privacy-Preserving AI Content Platforms. Zenodo. DOI: 10.5281/zenodo.20564543 Related publication: Stuart-Mueller, L. (2026). Constitutional Drift Detection and Multi-Agent Governance in Non-Custodial AI Financial Infrastructure. Zenodo. DOI: 10.5281/zenodo.20564598

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