为6G自主AI系统设计实时风险评估框架，解决动态治理难题。
The Economics of Autonomy: Real-Time Risk Indexing for Insurable AI-Driven 6G Systems
- 通过可编程治理框架实时量化风险指数，融合置信度、网络延迟等信号。
- 发现验证延迟超6G时限会引发安全风险，首次形式化该权衡关系。
- 适合研究6G安全、AI治理或保险模型的学者与工程师。
6G网络将无线基础设施转变为支持车联万物（V2X）、工业物联网（IIoT）和感知通信一体化（ISAC）的认知基底。在此范式下，自主智能体在毫秒级执行编排，传统静态治理框架无法满足风险管控需求。本文提出GIRAF（Governance-Integrated Risk and Assurance Framework），一种基于治理即代码（GaC）的实时风险量化与信任调节框架。GIRAF从可机器读取的运行时信号（包括认知置信度、网络抖动、验证延迟）中生成连续的综合风险指数（R_t）。核心贡献在于形式化了验证过期性权衡：当计算延迟超过6G时限时，安全机制反而会引入风险。我们证明GIRAF能识别‘置信差’——智能体报告的确定性与环境真实状态之间的偏差，并在条件恶化时触发自动安全边界。关键的是，GIRAF作为基础治理架构，将技术风险外化为可机读的遥测数据。通过微调大语言模型（LLM）的仿真验证，框架在保持运行完整性的同时，为多利益相关方责任追溯及动态保费计算提供了必要的精算基准。
原文摘要 · Abstract (English)
The transition to sixth-generation (6G) networks transforms wireless infrastructure into a cognitive substrate supporting Vehicle-to-Everything (V2X), Industrial IoT (IIoT), and Integrated Sensing and Communication (ISAC). In this paradigm, autonomous agentic AI performs orchestration at millisecond scales, rendering traditional static governance frameworks fundamentally inadequate for risk management. This paper introduces GIRAF(Governance-Integrated Risk and Assurance Framework), a Governance-as-Code (GaC) framework for real-time risk quantification and trust modulation in agentic 6G systems. GIRAF derives a continuous Aggregate Risk Index ($R_{t}$) from machine-readable runtime signals, including epistemic confidence, network jitter, and verification latency. A core contribution is the formalization of the verification staleness trade-off, where safety mechanisms induce risk if computational latency exceeds 6G deadlines. We demonstrate that GIRAF identifies 'Confidence Gaps' discrepancies between agent reported certainty and environmental ground truth, triggering automated safety envelopes when conditions deteriorate. Crucially, GIRAF serves as the foundational governance groundwork and conceptual 'glue' that externalizes these technical risks into machine-readable telemetry. Through simulations with fine-tuned Large Language Models (LLMs), we validate that the framework preserves operational integrity while providing the essential actuarial baseline required for multi-stakeholder liability attribution and dynamic premium quantification in the 6G ecosystem.
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