# Governed Auditable Decisioning Under Uncertainty: Synthesis and Agentic Extension

arXiv: https://arxiv.org/abs/2604.19112 · HTML: https://mlsanity.com/paper/2604.19112/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 21 Apr 2026.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 4 of 4)

- [Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems](https://mlsanity.com/paper/2102.04201/) (2021)
- [Faramesh: A Protocol-Agnostic Execution Control Plane for Autonomous Agent Systems](https://mlsanity.com/paper/2601.17744/) (2026)
- [Evidence Sufficiency Under Delayed Ground Truth: Proxy Monitoring for Risk Decision Systems](https://mlsanity.com/paper/2604.15740/) (2026)
- [Decision Trace Schema for Governance Evidence in Real-Time Risk Systems](https://mlsanity.com/paper/2604.09296/) (2026)

## Abstract (arXiv)

When automated decision systems fail, organizations frequently discover that formally compliant governance infrastructure cannot reconstruct what happened or why. This paper synthesizes an operational governance evidence framework -- structural accountability collapse diagnostics, decision trace schemas, evidence sufficiency measurement, and label-free monitoring -- into an integrated chain and analytically assesses its transferability across four decision system architectures. The cross-architecture comparison reveals a governance coverage gradient: deterministic rule engines achieve full DES-property fillability, hybrid ML+rules systems achieve partial fillability, classical ML systems achieve only minimal fillability, and agentic AI systems encounter structural breaks. We introduce the cascade of uncertainty, showing how governance failures propagate through serial dependencies between framework layers. For agentic systems, we identify three structural breaks -- decision diffusion, evidence fragmentation, and responsibility ambiguity -- and propose corresponding analytical extensions. Four propositions formalize the gradient, cascade compounding, delegation-depth effects, and extension sufficiency, establishing boundary conditions for the framework's valid operating envelope.