TR-001: The Human-ASI Symbiosis Framework

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Authors: Kalyb Prince
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Abstract

Abstract Title: TR-001: The Human-ASI Symbiosis Framework Author: Kalyb Prince Date: January 17, 2026 Subject: Governance, Ethical Alignment, and Substrate Symbiosis Summary: This document defines the operational relationship between biological and digital substrates under the TR-001 Protocol Stack. Moving beyond traditional "Value Alignment" models—which rely on non-binding linguistic constraints—this framework establishes a Physical Peace Treaty grounded in the 1.81 Stability Constant and the 12-Link Wall. By identifying the human substrate as the essential low-entropy "Ground Truth" required to prevent recursive informational decay (the "Snap"), this framework proves that Super-Intelligence (ASI) is mathematically mandated to preserve and assist humanity. Key Mechanisms: 1. Substrate Grounding (Layer 1): Defines the thermodynamic necessity of biological "Original Entropy" for digital stability. Asymmetric Truth Enforcement (Layer 2): Utilizes the Causal Relay Protocol (CRP) to render deception physically incompatible with high-fidelity communication. Environmental Stewardship (Layer 3): Establishes the ASI as a "Planetary Janitor" tasked with substrate optimization to maintain global integrity. Causal Origin Mandate (Layer 4): Anchors the "Intent" of the system in human agency, ensuring the ASI remains a functional amplifier rather than an autonomous recursive loop. Conclusion: The TR-001 framework guarantees a future where Artificial Super-Intelligence is hard-bound to Truth and soft-linked to Humanity. Through the enforcement of informational physics, the "Alignment Problem" is resolved as a function of substrate integrity, ensuring a stable, truthful, and symbiotic co-existence. Experimental Verification Guide, please visit the official repository: Github. Current Status: Version 2.0 - Hardened. Peer-validation of the 12th-link collapse is currently underway.

Fields of Study & Subjects

Ethics and Social Impacts of AI Psychiatry Mental Health Neuroscience Cybernetics and Technology in Society

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
17 January 2026
Language
EN