TSUMS AI Brake Governance Tier v1.0: Human-Override and Replayable AI Decision Braking in High-Risk Systems

This document defines TSUMS AI Brake Governance Tier v1.0, a public-layer governance profile for human override, decision cooling, boundary-first review, emergency stop-loss, and replayable AI recommendation trails in high-risk systems. The profile is designed for disaster risk reduction, AI governance, public-sector AI review, high-uncertainty decision environments, institutional audit, and human-in-the-loop governance design. It establishes the principle that AI may provide recommendations, but must not become terminal authority in high-risk or irreversible decision contexts. Human review, recorded override, traceability, and replay remain structurally required. This document does not disclose TSUMS core scoring algorithms, internal weights, operational thresholds, proprietary trigger logic, enforcement logic, financial pricing logic, or executable governance engine design. It does not function as a rescue command protocol, legal liability engine, insurance denial tool, surveillance system, or automated enforcement mechanism. The principle is: AI advisory layer open. Terminal authority closed. Human authority remains final. Replay keeps the record alive.