Overview

We like to tell a clean story about science where prediction improves because we get closer to truth. But there is another story: scientific prediction is a stack of survival heuristics that won a brutally long tournament. Our models are the descendants of approximations that didn't get their users killed. This book is a field manual for where that clean story breaks down. It explores ""non-ergodic hellscapes"" where averages are ghosts and one bad draw means ruin. It examines ""reflexive domains"" like markets and politics, where publishing a forecast changes the outcome because the system fights back. It challenges the comforting mantra that ""more data"" always solves the problem. Predicting the Unpredictable argues that rationality is often just a coping mechanism for high-uncertainty environments. It suggests that we need ""hybrid foresight"" systems that acknowledge the limitations of data-driven models and the surprising utility of ""oracles""-ritualized ways of accessing intuition, narrative, and emotional signals. The final section provides practical, dangerous protocols for real-world application, including: The 30-Second Triage for quick decisions. A protocol for when your model and your gut disagree. A short, nasty Red-Team script to attack your own plans. A personal danger checklist to run before acting on any prediction. This book will not teach you how to see the future. It will teach you how to remain dangerously, stubbornly alive in a world that refuses to be tamed.

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