Semantic Entropy
0ConceptA measure of the information loss or disorder introduced into a signal through transformation. Entropy from redundant generation, commitment degradation, or signal dilution.
Last updated: 2026-09-01Spec: CT Research Prospectus V.1
Definition
A measure of the information loss or disorder introduced into a signal through transformation. Entropy introduced by redundant generation, commitment degradation, or signal dilution.
Inputs
Original signal S. Transformed signal T(S).
Derived variables
Entropy = information loss between S and T(S). Redundancy in T(S). Signal-to-noise degradation.
Claim
Transformations introduce semantic entropy — the transformed signal carries less commitment and more noise than the original. This entropy is measurable.
Test
Measure information content and commitment in S and T(S). Compute the entropy difference.
Observable
Entropy values, information loss metrics, redundancy measures.
Falsifier
Transformations do not introduce semantic entropy (information is preserved perfectly).
Evidence
Related to the Conservation Law experiments which measure commitment degradation. Direct entropy measurement not yet conducted.
Limitations
Semantic entropy is distinct from Shannon entropy — it measures meaning loss, not bit-level information loss. Measurement methods are not standardized.
Lineage
Commitment Theory, Conservation Law, MO§ES™ architecture. Architecture: mos2es.com/concepts/conservation-law.