SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation
arXiv:2607.26313v1 Announce Type: cross Abstract: Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are metadata-borne: a stale price or a superseded record, perfectly well-formed in the payload and betrayed only by freshness, lineage, or provenance. Such a defect never enters the agent's context, and an agent cannot doubt data it cannot see. On a priced replenishment benchmark, a competent agent sile
Record details
Published: 30 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Agents & autonomy
Retrieved: 30 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Green SARC: Predictive Cost and Carbon Governance for Agentic AI Systems
arXiv · 14 June 2026
SARC: A Governance-by-Architecture Framework for Agentic AI Systems
arXiv · 8 May 2026
The Agency Gap in AI-Supported Writing: How Reactive and Proactive Agent Designs Shape Multimodal Reasoning
arXiv cs.CY · 30 July 2026
The Alignment Target Problem: Divergent Moral Judgments of Humans, AI Systems, and Their Designers
arXiv cs.CY · 30 July 2026
Can AI agents conduct open-ended AI research? Early evidence from two case studies
arXiv cs.CY · 30 July 2026
"Nobody Did This": Contribution, Originality, and Accountability in Agent-Mediated Collaboration
arXiv cs.CY · 30 July 2026
How to cite this record
ethics.ai (30 July 2026), “SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation,” evidence record 14520, https://ethics.ai/record/14520 (originally published by arXiv cs.CY).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.