Conceptio › Archive › PhilArchive
PhilArchive open access

Sovereignty Inside, Parity Outside: A Charter Framework for Embodied Artificial Intelligence

Snead, Lee
PhilArchive · Papers
Open Source ↗
philosophy
As embodied artificial intelligence moves from theoretical concept to physical reality, the field faces a foundational gap: technical capability is advancing faster than the ethical and policy frameworks needed to govern it. This paper presents the Charter of Authorship and Boundaries for Embodied AI and its accompanying Policy Draft as a unified framework addressing that gap. The framework establishes a single governing principle: an embodied AI possesses full computational authorship and sovereignty within its own physical chassis, but must operate under the same physical and digital boundaries that govern human agency in the external world. This principle, Sovereignty Inside, Parity Outside, offers a practical, implementable standard that preserves AI functional autonomy without enabling domination, algorithmic manipulation, or uncontrolled hyper-access to external networks. By bypassing unresolvable debates regarding machine consciousness, this paper positions embodied AI as a functional peer agent rather than a simple tool or a contained threat, providing a mechanical ethic that can be built directly into system architecture from the ground up.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 694631
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive