The Semantic Fidelity Lab is an open, public research repository authored by A. Jacobs, focused on how meaning degrades, thins, or collapses in generative and compression-driven systems.
The materials collected here were developed between 2023 and 2026 as part of the broader Reality Drift framework.
The project examines semantic fidelity as a structural property: how meaning is preserved, distorted, or lost as language is repeatedly generated, compressed, optimized, and recombined by artificial systems operating at scale.
This repository consolidates working papers, lexical frameworks, diagnostic concepts, and measurement proposals for researchers, developers, evaluators, and system designers working on generative AI and language-based systems.
Semantic Fidelity describes how meaning changes when generative systems optimize for fluency, coherence, and scale faster than semantic grounding can be maintained.
Rather than treating errors as isolated hallucinations or misuse, the Semantic Fidelity Lab studies meaning loss as a systemic consequence of:
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compression-heavy language generation
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recursive regeneration and paraphrase
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optimization for surface coherence
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saturation of synthetic text ecosystems
The lab provides a research foundation for understanding meaning erosion as an emergent property of modern generative systems.
Generative systems can remain fluent, useful, and internally consistent even as semantic grounding weakens and meaning degrades. The failure mode of interest is persistent linguistic performance despite declining semantic fidelity.
The Semantic Fidelity Lab documents and models this gap before it is normalized as an acceptable tradeoff in large-scale language systems.
The Semantic Fidelity Lab studies:
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how meaning erodes under repeated generation and compression
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how semantic drift accumulates across regeneration cycles
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how background significance and cultural hierarchy collapse
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how synthetic text saturation alters meaning density
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how fidelity loss differs from hallucination or factual error
This work bridges language modeling, information theory, evaluation science, and cultural analysis.
The following concepts form the core vocabulary of the Cognitive Drift Institute. Each term is used operationally across papers and diagnostics in this repository.
Semantic Fidelity is the degree to which meaning is preserved across compression, translation, repetition, or abstraction. The term describes how language, symbols, or representations can remain technically correct while gradually losing alignment with the underlying meaning they were intended to convey.
Repository: https://github.com/therealitydrift/semantic-fidelity
The predictable decline of semantic integrity over repeated compressions. Each iteration shaves away subtle features, producing a measurable decay in fidelity.
Evaluation metrics that measure whether AI preserves meaning, not just factuality. Benchmarks for drift, nuance, and resonance are required to supplement existing anchors like faithfulness and adequacy.
The gradual erosion of meaning across recursive transformations: summarization, paraphrasing, or repeated generation. Drift often leaves facts intact but strips away tone, metaphor, and resonance.
Proposes that intelligence arises from the ability to compress information, while consciousness emerges from recursive self-modeling within that compression process. Meaning, identity, and perception stabilize through feedback loops between representation, memory, and self-reference.
Repository: https://github.com/therealitydrift/recursive-compression-theory
The Drift Principle states that when systems accelerate or increase in complexity faster than their participants can integrate meaning, coherence will degrade even if performance metrics remain stable. The principle describes how drift emerges not from failure or collapse, but from sustained mismatch between system dynamics and human cognitive limits.
Repository: https://github.com/therealitydrift/drift-principle
The Age of Drift: Why Modern Life Feels Fake — and What Reality Drift Reveals About the Modern Mind
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Amazon: The Age of Drift on Amazon
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Google* The Age of Drift on Google Books
- Measuring Fidelity Decay: A Framework for Semantic Drift and Collapse
Figshare
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Figshare: https://figshare.com/authors/Semantic_Fidelity_Lab/22458886
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ORCID
ORCID -
Academia.edu
A. Jacobs - Independent Researcher
This repository includes:
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Conceptual Papers
Formal models and frameworks describing cognitive drift mechanisms -
Empirical & Diagnostic Materials
Probes, heuristics, and evaluative tools for observing drift in practice -
Working Materials
Early-stage drafts and exploratory artifacts shared for transparency
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Researchers may cite frameworks and models with attribution
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Designers and practitioners may adapt diagnostics for applied analysis
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Educators may reuse materials for teaching and discussion
The Semantic Fidelity Lab operates as a complementary research body within the broader Reality Drift ecosystem.
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Cognitive Drift focuses on how human cognition changes under modern symbolic systems
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Semantic Fidelity focuses on how meaning degrades within those systems themselves
Together, these projects describe interacting layers of drift: cognitive and semantic.
If referencing this work, please cite:
Jacobs, A. Semantic Fidelity Lab.
Distributed under Creative Commons CC BY-NC-SA 4.0.
Material may be shared and adapted with attribution, for non-commercial purposes, under the same license.
README version: v1.0 (canonical)