THE CARPET FALLACY: A STRUCTURAL FAILURE MODE IN SYNCHRONIC ANALYSIS OF DIACHRONIC PROCESSES AND ITS EXPONENTIAL AMPLIFICATION IN AI-ASSISTED ANALYSIS

This paper identifies and characterizes the Carpet Fallacy: a structural failure mode introduced when sequential processes are analyzed from their complete records. The analyst observes the finished pattern from above rather than reconstructing the internal logic of the process as it was generated step by step. The resulting analysis may be formally correct — internally consistent and logically coherent — while being substantially misaligned with the actual logic that produced the process. This misalignment is invisible in the output and undetectable by standard quality criteria. The paper distinguishes the fallacy from hindsight bias, extends it to peer review as a case of the same structural problem, and argues that AI systems face an exponentially amplified version due to their default synchronic processing mode. The corrective principle — diachronic re-entry, retracing the calculation from inside rather than verifying the result from outside — requires deliberate methodological and architectural intervention. Safety implications are identified across clinical, legal, military, and scientific domains.