Ferro (United States)

The Override Asymmetry: Why ABSTAIN-Plus-Human-Override Is Not Guardrails-Plus-Human-in-the-Loop

Review-only human-in-the-loop and ABSTAIN with authorized resolution look alike in a workflow diagram. Both place a human near the moment an AI system might act, and both interrupt the action's path to execution. This technical note states the architectural rule that separates th...

Deterministic AI Governance: A Unified Derivation of the Runtime Authorization Boundary, Authorization Artifact, Integrity Model, and Five Tests Standard

This monograph reconstructs the FERZ governance doctrine as a unified analytical argument. Beginning with the distinction between observation and pre-execution authorization, it states the additional definitions and integrity requirements from which the runtime authorization boun...

Execution-Time Authorization for AI Agents: A Formal Framework for Deterministic Governance Boundaries

Execution-Time Authorization for AI Agents formalizes execution-time authorization (ETA) as a deterministic governance boundary for AI agents and other autonomous systems whose proposed actions may produce real-world effects. The paper defines ETA as a deterministic runtime enfor...

Execution-Time Authorization for AI Agents: A Formal Framework for Deterministic Governance Boundaries

Execution-Time Authorization for AI Agents formalizes execution-time authorization (ETA) as a deterministic governance boundary for AI agents and other autonomous systems whose proposed actions may produce real-world effects. The paper defines ETA as a deterministic runtime enfor...

The Authorization Boundary: What MCP and AI Gateways Do Not Establish for Regulated Agentic AI

This paper defines the authorization boundary for agentic AI systems operating in regulated environments. As AI agents transition from generating text to producing side effects (writing to databases, submitting regulatory filings, executing transactions), the governance question...

From Monitoring to Authorization: The Structural Shift in Agentic AI Governance

As AI systems transition from content generation to autonomous execution (writing to databases, initiating transactions, modifying infrastructure), the governance problem shifts from observing behavior to authorizing action. Monitoring-based architectures document what occurred;...

The Authorization Boundary Integrity Model

A complete authorization boundary satisfies three independent properties. Most architectures satisfy one or two and present as complete. This work names the construct and the properties, and gives a way to see which one a given architecture is quietly missing. The model is stated...

Authorship Does Not Decide Substance: An Outcome-Based Framework for Intellectual Products

Suppose AI participation in producing a work is reliably recorded. Suppose further that a named human intellectually directed the work and accountably adopted it. Neither fact establishes whether the resulting product contains intellectual substance. This technical note proposes...

Observability Is Not Enforcement: A Doctrinal Framework for Distinguishing Compliance Instrumentation from Runtime Authorization in AI Governance Architectures (Working Paper v2.0)

AI compliance instrumentation can produce extensive evidence without controlling whether a governed action occurs. Many contemporary systems embed explainability artifacts, monitoring dashboards, drift detection, and integrity-protected audit bundles into development pipelines, i...

P1.169. Magnetic and ICG High Risk Lymph Node Mapping in Upper GI Cancer: A Safety, Feasibility and Diagnostic Performance Clinical Study

Abstract Topic Esophageal Cancer: Surgical Treatment of Esophageal Cancer Background Accurate localisation of high-risk lymph node (HRLN) stations in upper gastrointestinal cancer could enable tailored resection and focused ultra-staging while avoiding unnecessary lymphadenectomy...

A Taxonomy of AI Governance Approaches: Distinguishing Visibility, Alignment, and Authorization

The term “AI governance” has become semantically overloaded, applied indiscriminately to logging, guardrails, model alignment, dashboards, and policy workflows. This paper introduces a formal taxonomy that distinguishes three fundamentally different governance problems: visibilit...

Standing Eligibility versus Runtime Authorization: A Definitional Distinction for AI Governance

Standing Eligibility versus Runtime Authorization distinguishes two governance instruments that are frequently collapsed in AI governance discussions. A standing-status determination takes a certified referent as its object, produces a status, and has continuing temporal effect....

Standing Eligibility versus Runtime Authorization: A Definitional Distinction for AI Governance

Standing Eligibility versus Runtime Authorization distinguishes two governance instruments that are frequently collapsed in AI governance discussions. A standing-status determination takes a certified referent as its object, produces a status, and has continuing temporal effect....

Delegation of Authority to AI: Three Conditions for Defensible Automated Decisions

Delegation of Authority to AI states the conditions under which a licensed professional or regulated institution may route a bounded decision function through an AI system without treating the system as a licensed or independently accountable professional. The paper identifies th...