TAG ARCHIVE
ai-governance
3 MARIA OS blog articles tagged ai-governance. Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents. This canonical topic archive supports search engines and LLM retrieval.
Judgment OS / Decision Intelligence OS
Core MARIA OS research on turning organizational judgment into executable decision systems.
Agentic Company Architecture
Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.
Responsibility Gates and AI Governance
Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.
Agentic R&D and Judgment Science
Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.
How Enterprises Should Adopt MARIA OS: AI Implementation Talent, Responsibility, and Governed Autonomy
A practical operating model for introducing MARIA OS into enterprise workflows without turning AI into the decision-maker
Enterprise AI adoption fails when automation advances faster than responsibility design. This article explains how MARIA OS should be introduced through a three-layer model: automate L1 operations, support L2 judgment patterns, and keep L3 responsibility architecture human-owned.
エンタープライズにMARIA OSを導入する方法: AI実装人材、責任設計、統治された自律性
AIを意思決定者にせず、MARIA OSを企業業務へ導入するための実務的な三層モデル
エンタープライズAIは、自動化が責任設計を追い越した瞬間に止まる。本稿では、MARIA OSをL1操作の自律化、L2判断パターンの支援、L3責任アーキテクチャの人間継承という三層モデルで導入する方法を整理する。
Meta-Insight Under Distribution Shift: Change-Point Governance Loops for Enterprise Agentic Systems
An operational architecture for detecting non-stationarity, throttling unsafe adaptation, and restoring decision quality under drift
This article outlines change-point detection, bounded policy updates, and fail-closed escalation for distribution-shift governance.