← Back to all news
arXiv AI By Yue Zhao, Jiate Li, Li Li, Yi Nian, Jinbo Liu, Xiaolin Zhou, Xiyang Hu

Auditable Claims about AI Agents

Read the original on arXiv AI →

The paper "Auditable Claims about AI Agents" argues that for a claim about an AI agent to be verifiable, it must explicitly state the agent’s policy, scope, the records that would confirm the claim, and who is responsible for those records. It extends the Auditable Agents framework by adding conditions of independent record coverage, action‑specific authorization, and completeness beyond integrity, and demonstrates the approach with a claim‑check table applied to six common claims. The authors provide a worked example and practical guidance for operators, buyers, auditors, and standard setters.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

Related stories

arXiv AI
Sep 17

Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI

The paper proposes an independence‑graded audit protocol for agentic AI systems, arguing that independence should be evaluated along three orthogonal axes: principal independence, substrate independence, and evidence independence. It introduces a seven‑step protocol based on the beta‑factor model from reliability engineering, demonstrates its application through a structural detectability analysis and a Monte Carlo study, and maps the framework to relevant regulatory standards such as the EU AI Act, ISO/IEC 42006, and UK public‑sector guidance.

By Mohamed Chahine Ghanem
agentssafety
More like this →
arXiv AI
Oct 1

Trust Is Not a Score: Runtime Assurance Contracts for High-Risk AI Agents

The paper introduces Runtime Assurance Contracts (RAC) as a formal policy framework for high‑risk AI agents, addressing the "assurance‑transition gap" by binding autonomy boundaries, component eligibility, evidence state, transition policy, human‑review capacity, and non‑compensatory gates. RAC allows soft metrics to influence routing while mandating retries, switches, escalations, deferrals, or stops when mandatory gates fail or are unknown, ensuring aggregate performance cannot alone authorize action. The authors define the contract, evidence record, permission rule, and five invariants, and evaluate RAC through deterministic failure‑injection studies, hand‑authored traces, and a prospective synthetic holdout, comparing it to score‑only and restricted protocol baselines.

By Serhii Zabolotnii
llmsagentsbenchmarkssafety
More like this →