CANON Named Owner Principle · every clinical AI deployment requires two named persons in the audit trail — a Governance Owner at Layer 4 and a Decision Owner at the bedside, not one substituting for the other WORKING PAPER №01 The handoff that isn’t · how clinical AI escapes accountability · Mo Johnson, MD MBA EVIDENCE Duke-Margolis 2026 · most US health systems have not named who owns the clinical AI decision when something goes wrong CANON Layer 4 · Clinical AI Governance at the bedside · the layer where the named owner has to live FRAMEWORK Clinical AI Accountability Canvas™ · the diagnostic framework distinguishing Clinical AI Governance from General AI Governance EVIDENCE Stanford MedAgentBench · agentic systems already executing clinical recommendations without a named adjudicator on the chart CANON The Two Inputs · internal data the institution audits · external data the model was trained on, rarely audited at the deployment site CITATION MedicoVigilance™ Issue 6 · The Layer With No Name · 1,627 institutional subscribers CANON The Accountability Gap · the structural failure point where AI stops and the physician starts FRAMEWORK Mind the 9 Blocks™ · the nine institutional blocks that must be in place before clinical AI deployment EVIDENCE npj Digital Medicine · the four-layer governance cascade · most institutions have built the first two layers and left Layer 4 unbuilt PORTFOLIO Tangibley Health Inc. · MedicoVigilance™ Surface 1 · the named-owner architecture deployed in clinical workflow CANON Named Owner Principle · every clinical AI deployment requires two named persons in the audit trail — a Governance Owner at Layer 4 and a Decision Owner at the bedside, not one substituting for the other WORKING PAPER №01 The handoff that isn’t · how clinical AI escapes accountability · Mo Johnson, MD MBA EVIDENCE Duke-Margolis 2026 · most US health systems have not named who owns the clinical AI decision when something goes wrong CANON Layer 4 · Clinical AI Governance at the bedside · the layer where the named owner has to live FRAMEWORK Clinical AI Accountability Canvas™ · the diagnostic framework distinguishing Clinical AI Governance from General AI Governance EVIDENCE Stanford MedAgentBench · agentic systems already executing clinical recommendations without a named adjudicator on the chart CANON The Two Inputs · internal data the institution audits · external data the model was trained on, rarely audited at the deployment site CITATION MedicoVigilance™ Issue 6 · The Layer With No Name · 1,627 institutional subscribers CANON The Accountability Gap · the structural failure point where AI stops and the physician starts FRAMEWORK Mind the 9 Blocks™ · the nine institutional blocks that must be in place before clinical AI deployment EVIDENCE npj Digital Medicine · the four-layer governance cascade · most institutions have built the first two layers and left Layer 4 unbuilt PORTFOLIO Tangibley Health Inc. · MedicoVigilance™ Surface 1 · the named-owner architecture deployed in clinical workflow

TOPICS

The territory of accountability in clinical AI.

Six subject areas define what GPe Research Publications takes up and what it leaves to other venues.

Editorial taxonomy

The publication works inside a specific territory. The questions it takes up are structural, not technical. The boundary is decision ownership. Anything upstream of the decision belongs to model developers, regulators, and clinical informatics teams. Anything downstream belongs to malpractice systems and tort law. GPe Research Publications works the layer in between — where the AI stops and the institution has to stand behind the output.

The six subject areas below organize that layer. Each defines a recurring locus of failure or a recurring instrument for closing it. Papers are tagged accordingly and accumulate over time into the institutional record of the field.

Subject areas

Accountability Architecture

The structural design of who owns what when clinical AI produces an output. Named owners, audit trails, escalation paths, decision traceability.
Clinical AI Governance

The institutional layer above deployment. Board oversight, committee structure, policy frameworks, vendor management, procurement standards.
Named Owner Principle

The editorial spine of the publication. The case for mandatory professional ownership of every AI generated recommendation, above the clinician in the audit trail.
Audit Trail Integrity

Decision traceability at the point of care. What gets logged, what gets named, what survives discovery, what holds up in litigation.
Regulatory Standing

The interface between clinical AI deployment and federal regulators, state medical boards, accreditation bodies, and tort law. Where institutional liability lives.
Diagnostic Frameworks

The instruments the publication develops to name where accountability breaks. The Clinical AI Accountability Canvas™. Mind the 9 Blocks™. MedicoVigilance™.

What this publication does not cover

The publication does not run model performance benchmarks. It does not evaluate clinical AI products. It does not adjudicate vendor claims. It does not publish opinion that is not grounded in clinical, legal, or institutional standing. The work upstream of the decision belongs to model developers and clinical informatics journals. The work downstream of harm belongs to malpractice law and patient safety literature. The publication holds the layer in between.