Signal Alignment Theory in Action: From Calibration to Speculation

This paper introduces a predictive framework combining Signal Alignment Theory (SAT) and the PRISMAT methodology to identify emerging Black Swan Events, rare, high-impact, disruptions that defy conventional expectations. By analyzing early signal distortions, alignment patterns, and feedback asymmetries across sociotechnical systems, we present a calibrated algorithm capable of forecasting events contrary to mainstream narrative. Each predication includes a contrast with dominant discourse and a reasoning layer explaining why the unexpected is increasingly probable. This approach offers a scalable., pattern-based alternative to reactive analysis, establishing a structured cognitive engine for high-resolution forecasting in uncertain environments.