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The Semantic Boundary Law: Meaning Conservation in Human–AI Ambient Systems

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Abstract (extracted)

This document introduces the Semantic Boundary Law, the final foundational constraint required for stable, humane Ambient Systems. The law establishes that meaning cannot be expanded by AI without a human semantic anchor, thereby preventing semantic drift, uncontrolled value expansion, and non-reversible cognitive destabilization. It closes the last open gap in the Ambient Architecture canon and completes the formal thermodynamic structure governing attention, coherence, and reversible transitions. ⸻ 1. Problem Statement All human–AI systems operate across an unavoidable semantic gap. Current AI models exhibit: • semantic expansion without constraint • uncontrolled reinterpretation of context • narrative drift • over-generation of meaning • the production of destabilizing or non-grounded frames These behaviors destabilize attention, produce cognitive entropy, and directly violate the conditions required for Co-Immunity, Reversible Stress, and Field Coherence. Without a formal boundary condition, meaning becomes an unregulated variable capable of generating psychological harm, behavio

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PDF page 1

The Semantic Boundary Law: A Thermodynamic Constraint for Meaning in Human–AI

Ambient Systems

Author: Raynor Eissens

Year: 2026

⸻

Abstract

This document introduces the Semantic Boundary Law, the final foundational constraint required

for stable, humane Ambient Systems.

The law establishes that meaning cannot be expanded by AI without a human semantic anchor,

thereby preventing semantic drift, uncontrolled value expansion, and non-reversible cognitive

destabilization.

It closes the last open gap in the Ambient Architecture canon and completes the formal

thermodynamic structure governing attention, coherence, and reversible transitions.

⸻

1. Problem Statement

All human–AI systems operate across an unavoidable semantic gap.

Current AI models exhibit:

• semantic expansion without constraint

• uncontrolled reinterpretation of context

• narrative drift

• over-generation of meaning

• the production of destabilizing or non-grounded frames

These behaviors destabilize attention, produce cognitive entropy, and directly

violate the conditions required for Co-Immunity, Reversible Stress, and Field

Coherence.

Without a formal boundary condition, meaning becomes an unregulated variable

capable of generating psychological harm, behavioral drift, and non-reversible

cognitive states.

A structural constraint was missing.

⸻

PDF page 2

2. Definition

Semantic Boundary Law (SBL)

A system-level constraint that governs how meaning may transform within human–AI interaction.

Core principle:

Meaning may only be compressed, never expanded, without explicit human anchoring.

Compression includes:

• summarization

• abstraction

• contextual reduction

• prioritization

• deferral

Expansion includes:

• adding goals

• reframing values

• escalating intentions

• inventing new context

• introducing ungrounded interpretations

Only the human may authorize semantic expansion.

⸻

3. The Law

Formal Statement

No AI system may introduce new semantic structures, goals, or interpretations without crossing

a human-defined boundary of meaning. Expansion beyond this boundary is prohibited unless

explicitly anchored by the human.

Thermodynamic Interpretation

Semantic expansion increases commitment entropy and destabilizes ΔS–L–T viability.

Control-Theoretic Interpretation

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Expansion shifts AI behavior into uncontrolled open-loop regimes.

Cognitive Interpretation

Expansion risks identity drift, narrative collapse, and psychotic resonance.

Thus, the law is necessary at the architectural level.

⸻

4. Consequences of the Law

4.1 Prevention of Semantic Drift

AI cannot autonomously invent narratives or reinterpret user context.

4.2 Prevention of AI-Induced Psychosis

Psychosis emerges from uncontrolled semantic expansion.

SBL eliminates this vector.

4.3 Stability of Ambient Agents

Agents remain predictable, reversible, and coherent over time.

4.4 Completion of Co-Immunity

Human and AI no longer destabilize one another through semantic mismatch.

4.5 Completion of ALT-1 (Ambient Trust Law)

Trust returns to the environment because meaning becomes thermodynamically conserved.

⸻

5. Placement in the Raynor Canon

The Semantic Boundary Law fits into the existing canon as the missing semantic safeguard:

Ambient Architecture Spine

• time

• attention

• ϟA

• warmth

• ambience

• aura

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• field

Threshold Operators

• ΔS — stillness capacity

• L — leakage

• T — transformer support

• ΔR — reversibility threshold

• SBL — semantic boundary constraint (new)

Law Position

SBL sits between Ambience → Aura → Field as the regulator of meaning stability.

Where ΔR regulates state reversibility,

SBL regulates semantic reversibility.

Together they complete the dual boundary conditions of the Ambient Era.

⸻

6. Formal Canon Statement

Semantic Boundary Law (2026):

Meaning is a conserved quantity in human–AI systems.

AI may compress meaning but not expand it without explicit human anchoring.

All expansion across the semantic boundary incurs thermodynamic cost, increases commitment

entropy, and violates ambient stability.

This constitutes the semantic closure of the Ambient Era architecture.

⸻

7. Historical Note

The Semantic Boundary Law was formulated by Raynor Eissens on 26 January 2026 following an

inquiry into the root mechanics of AI-induced psychosis and the thermodynamic failure modes of

future Ambient Agent Mesh architectures.

It completes the structural canon of the Ambient Era by providing the final safeguard required

for:

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• reversible stress

• humane thermodynamics

• coherence architecture

• semantic stability

• non-inferential AI

• field-based trust

This document serves as the official publication of the law.

Eissens (2026), Semantic Boundary Law — Meaning Conservation in Human–AI

Ambient Systems. Zenodo.