AI Alignment Failures: Visualizing Drift, Compression, and Meaning Loss
A collection of visual frameworks from the Semantic Fidelity Lab.
These visuals map how meaning is preserved, distorted, and degraded as language is compressed, generated, and transformed across modern systems.
Each framework isolates a specific structural pattern, from proxy optimization and semantic drift to the recursive interaction between language and cognition. Together, they shift focus away from surface-level errors and toward the deeper mechanisms that shape alignment, trust, and understanding.
Taken as a whole, these visuals establish a shared language for identifying when systems remain operational while gradually losing connection to the reality they were designed to represent.
Visuals – Reality Drift, Fidelity Decay, and Semantic Compression
Reality Drift: When Systems Optimize Proxies Instead of Reality (PDF)
Maps how reward hacking, hallucination, specification gaming, and misalignment emerge from the same underlying pattern: systems optimizing proxies while drifting away from real-world grounding.
[Slideshare]
The Four Dimensions of Fidelity Decay (PDF)
Breaks down how meaning erodes over time through lexical decay, semantic drift, ground erosion, and semantic noise, showing how language can remain fluent while losing structure and context.
[Slideshare]
The Language–Cognition Loop (PDF)
Illustrates how perception, cognition, language, and AI systems form a recursive feedback loop, where thought is shaped through cycles of generation, reflection, and reinterpretation.
[Slideshare]
Language as Cognitive Exhaust (PDF)
Reframes language as the compressed residue of deeper cognitive processes, highlighting the gap between thought and expression where meaning is reduced before it is ever communicated.
[Slideshare]
Accuracy vs. Semantic Fidelity (PDF)
Distinguishes between correctness and understanding in AI systems, showing how traditional evaluation metrics overlook whether meaning and intent are preserved across transformations.
[Slideshare]
Additional Resources
- Semantic Fidelity Glossary
- Semantic Fidelity Canonical Framework (PDF)
- Failure Modes in LLM Systems
- Preserving Meaning in the Age of Artificial Intelligence
Note: This page is part of the Semantic Fidelity Lab, a focused reference archive on meaning preservation, semantic drift, and evaluation failure in AI systems. This site functions as a reference layer for selected concepts, summaries, and document collections connected to the broader Reality Drift framework by A. Jacobs.