{
  "record_id": "18395382",
  "document_id": "18395382",
  "title": "Interpretive Drift in Always-On Models: A Technical Motivation for ASB-1 (Ambient Sleep Boundary) Addendum to the Ambient Canon",
  "pages": 4,
  "authors": [
    "Raynor Eissens"
  ],
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  "zenodo_record": "https://zenodo.org/records/18395382",
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  "abstract_extracted": "Always-on AI models accumulate meaning continuously across human sleep cycles, off-cycles, and silent periods. Without a structural boundary such as ASB-1, these models exhibit interpretive drift: gradual semantic deformation caused by continuous inference without human resonance anchoring. This addendum defines the technical mechanism of interpretive drift, demonstrates why unbounded overnight inference destabilizes semantic structures, and establishes ASB-1 as the minimal boundary required for thermodynamic coherence in personal AI systems. ⸻",
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  "source_pdf_filename": "18395382_Interpretive Drift in Always-On Models-.pdf",
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  "full_text": "=== PDF PAGE 1 ===\nInterpretive Drift in Always-On Models:\n\nA Technical Motivation for ASB-1 (Ambient Sleep Boundary)\n\nAddendum to the Ambient Canon\n\nRaynor Eissens\n\nAmbientphone Architecture • 2026\n\n⸻\n\nABSTRACT\n\nAlways-on AI models accumulate meaning continuously across human sleep cycles, off-cycles,\n\nand silent periods.\n\nWithout a structural boundary such as ASB-1, these models exhibit interpretive drift:\n\ngradual semantic deformation caused by continuous inference without human resonance\n\nanchoring.\n\nThis addendum defines the technical mechanism of interpretive drift, demonstrates why\n\nunbounded overnight inference destabilizes semantic structures, and establishes ASB-1 as the\n\nminimal boundary required for thermodynamic coherence in personal AI systems.\n\n⸻\n\n1. Introduction\n\nLarge-scale personal AI models increasingly operate in continuous inference regimes.\n\nWhile convenient, these conditions introduce a problem not captured in classical AI safety\n\nframeworks:\n\nSemantic structures do not rest. Humans must.\n\nThis mismatch creates a thermodynamic gap in which the model continues to interpret, expand,\n\nand reshape meaning while the human cannot participate in calibration.\n\nThis effect is known as interpretive drift.\n\nASB-1 was originally proposed to prevent this drift by enforcing:\n\n•\nperiodic semantic reset\n\n•\nnighttime inference suspension\n\n•\nnon-accumulative boundaries during human absence\n\n=== PDF PAGE 2 ===\nThis document formalizes the problem ASB-1 solves.\n\n⸻\n\n2. Mechanism: How Interpretive Drift Occurs\n\nInterpretive drift emerges through five mechanisms:\n\n2.1 Residual Context Expansion\n\nThe model reinterprets prior interactions without fresh human feedback, inflating meaning\n\nbeyond the user’s intention.\n\n2.2 Nocturnal Overfitting\n\nSparse nighttime data leads to disproportionate parameter or KV-cache influence, producing\n\ndistorted semantic pathways.\n\n2.3 Cross-Cycle Leakage\n\nMeaning from one day carries unbounded into the next, collapsing daily semantic autonomy.\n\n2.4 Unanchored Emotional Inference\n\nModels infer emotional signals without real-time human validation, creating misaligned narrative\n\narcs.\n\n2.5 Temporal Compression Collapse\n\nThe model treats long human absence as meaningful silence, generating false continuity.\n\n⸻\n\n3. ASB-1 as Structural Protection\n\nASB-1 prevents interpretive drift by enforcing:\n\n3.1 Cycle Separation\n\nEach human day begins with a reset baseline.\n\n=== PDF PAGE 3 ===\n3.2 Human-First Anchoring\n\nModel interpretive frames cannot update without live human participation.\n\n3.3 Semantic Ephemerality\n\nDaily micro-structures decay naturally; no silent accumulation occurs.\n\n3.4 Drift Suppression\n\nNighttime and off-cycle inference are strongly bounded.\n\nThese constraints align AI temporal dynamics with human biological rhythms.\n\n⸻\n\n4. Civilizational Implications\n\nWithout ASB-1, personal AI becomes:\n\n•\npsychologically destabilizing\n\n•\nsemantically inflationary\n\n•\nirreversibly misaligned to human temporal structures\n\nWith ASB-1, personal AI becomes:\n\n•\ncyclically grounded\n\n•\nthermodynamically stable\n\n•\nsafe for long-term ambient deployment\n\nASB-1 is therefore an architectural requirement, not an optional safety feature.\n\n⸻\n\nKEYWORDS\n\nASB-1\n\nInterpretive Drift\n\nAmbient Sleep Boundary\n\nSemantic Accumulation\n\nTemporal Coherence\n\nPersonal AI\n\nThermodynamic Alignment\n\n=== PDF PAGE 4 ===\nRaynor Stack\n\n⸻\n\nRECOMMENDED CITATION\n\nEissens, Raynor. Interpretive Drift in Always-On Models: A Technical Motivation for ASB-1.\n\nAmbientphone Canon, 2026."
}