A long-form systems essay arguing that machine learning fails when used as an automated decision-maker in unstable environments. It reframes ML as an early-warning instrument that exposes pressure, instability, and shrinking intervention windows, preserving human judgment instead of replacing it with late, brittle decisions.

A long-form systems essay arguing that most metrics fail because they measure outcomes instead of accumulated pressure. It reframes collapse as a consequence of debt, buffer depletion, and delayed feedback, and explains why early warning depends on measuring pressure rather than predicting final events.

CoreSense Risk Awareness Module (RiskAM)

This repository provides a model‑agnostic, uncertainty‑aware framework for transportation mode‑choice prediction via Inductive Mondrian Conformal Prediction (IMCP). While XGBoost is used as the base classifier in our experiments, the conformal wrapper is compatible with any predictive model.