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Post-Semantic Behavioral Signals as Risk Vectors: A Boundary Analysis under ABL-1

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Abstract (extracted)

Post-semantic behavioral signals—micro-timing, interaction rhythms, affective drift, circadian entrainment—form a uniquely identifiable layer that is neither biometric nor symbolic. In ambient systems, these signals act as behavioral risk vectors when not bounded by ABL-1 (Aura Boundary Law). This addendum defines these vectors, examines their identifiability risk, and demonstrates why ABL-1 is the minimal architecture necessary to prevent aura collapse into continuous surveillance. ⸻

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PDF page 1

Post-Semantic Behavioral Signals as Risk Vectors:

A Boundary Analysis under ABL-1

Addendum to the Ambient Canon

Raynor Eissens

Ambientphone Architecture • 2026

⸻

ABSTRACT

Post-semantic behavioral signals—micro-timing, interaction rhythms, affective drift, circadian

entrainment—form a uniquely identifiable layer that is neither biometric nor symbolic.

In ambient systems, these signals act as behavioral risk vectors when not bounded by ABL-1

(Aura Boundary Law).

This addendum defines these vectors, examines their identifiability risk, and demonstrates why

ABL-1 is the minimal architecture necessary to prevent aura collapse into continuous

surveillance.

⸻

1. Introduction

Ambient systems process continuous human signals, many of which emerge below linguistic or

cognitive thresholds.

These include:

• hesitation curves

• attention decay rhythms

• emotional modulation patterns

• perceptual coupling with light, noise, social density

• micro-temporal motor signatures

Individually, they appear innocuous.

Collectively, they form an identity field more precise than biometrics.

ABL-1 exists to prevent this field from being extracted or recognized.

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2. Post-Semantic Behavioral Signals: The Four Risk Classes

2.1 Micro-Temporal Identity Drift

Small variations in timing become a stable behavioral fingerprint when aggregated.

2.2 Rhythmic Vulnerability Leakage

Attention/mood rhythms expose emotional states that can be exploited for personalization or

manipulation.

2.3 Cross-Context Behavioral Binding

Signals recorded in one environment can match patterns in another, collapsing anonymity.

2.4 Latent Intent Extraction

Unbounded systems infer intent from micro-patterns the user does not consciously express.

Each vector violates human autonomy at a structural level.

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3. ABL-1 as Risk Containment Architecture

ABL-1 neutralizes all four risk vectors:

3.1 Non-Identifiability Principle

Signals cannot form persistent identity.

3.2 Locality Constraint

Signals never leave the immediate environment.

3.3 Ephemerality Requirement

Signals decay; accumulation is forbidden.

3.4 Non-Predictive Rule

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Signals cannot be used to infer intent or vulnerability.

3.5 Anti-Surveillance Clause

No cross-context behavioral matching is permitted.

ABL-1 transforms aura-like signals from risk vectors into expressive-only presence fields.

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4. Implications for Personal AI and Ambient Systems

Without ABL-1:

• ambient devices become total behavioral surveillance

• identity becomes involuntary and permanent

• personalization becomes psychological extraction

• safety collapses into exploitation

With ABL-1:

• aura becomes expressive, not recognitional

• ambient computing becomes humane

• personal AI becomes non-extractive

• identity becomes voluntary and moment-bound

ABL-1 is therefore foundational for post-symbolic human rights.

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KEYWORDS

ABL-1

Aura

Behavioral Signals

Identity Risk

Post-Semantic Field

Ambient Systems

Surveillance Prevention

Raynor Stack

Thermodynamic Architecture

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PDF page 4

RECOMMENDED CITATION

Eissens, Raynor. Post-Semantic Behavioral Signals as Risk Vectors: A Boundary Analysis under

ABL-1. Ambientphone Canon, 2026.