Predictive trial estimates breach hazard and buffer exhaustion across various systems, suggesting improved structural integrity management.
This paper introduces Predictive Structural Intelligence as a time-bound extension of the Structural Intelligence framework. Its central claim is that structures do not usually fail simply because mismatch exists; they fail when mismatch accumulates faster than repair can bind. The paper therefore shifts SI from static diagnosis toward breach-hazard estimation: the disciplined assessment of whether contradiction is being metabolized into binding repair quickly enough to prevent structural debt, buffer exhaustion, burden export, hysteresis, and synthetic trace from forcing contact in a harder form. It proposes a state sequence from answerable operation to compensation, fluency masking, debt-financed stability, theater-stabilization, brittleness, flickering, crisis, and possible repair or fragmentation. It also defines predictive variables including drift velocity, contact half-life, contradiction recovery lag, repair velocity, maintenance inflation, hidden-holder depletion, burden export velocity, synthetic trace discount, and binding strength. Drawing on resilience engineering, graceful extensibility, critical-transition research, cybernetics, and system safety, the paper treats prediction as a bounded, falsifiable, and downgrade-governed practice rather than deterministic prophecy. Its key methodological rule is that no predictive claim can be marked Verified when apparent repair depends mainly on hidden-holder labor, unverified AI trace, manual rescue, or synthetic documentation. The result is a practical architecture for estimating structural exhaustion across AI systems, institutions, relationships, infrastructure, and organizational life.
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Vladisav Jovanovic (2026) studied this question.
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