面向可信系统的生成式人工智能——迈向健康检查模型
Generative AI for trustworthy systems - Towards a health check model
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- Chalmers University of Technology（查尔姆斯理工大学）
- University of Hawai’i（夏威夷大学）
- University of L’Aquila（拉奎拉大学）
- Malmö University（马尔默大学）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
本文提出可信自主健康检查模型，一种多维诊断工具，用于评估组织在生成式人工智能辅助软件工程中的信任建立，通过八个维度和四种信任范式支持跨组织比较与配置对齐。
中文摘要 AI 辅助
生成式人工智能在软件密集型系统中的采用正在迅速推进，但当前的分析工具——主要是单维成熟度模型——将重要的配置差异压缩到单一渐进轴上。基于对电信、汽车、国防、航空、银行、能源、政府和企事业软件服务领域十八位资深从业者的归纳性访谈研究，本文提出了可信自主健康检查模型：一种结构化的多维工具，用于刻画组织如何在生成式人工智能辅助软件工程中建立信任。该模型将八个基于实证的维度组织为系统层（智能体权限范围、保障机制、数据可信度、架构遏制、可追溯性与可理解性）和组织层（治理、人工监督姿态、 workforce 能力可持续性），每个维度采用五级序数标度。一个跨领域的四信任范式叠加层——操作型、工程型、统计型和遏制型——捕捉了信任是如何建立的，补充了刻画什么必须可信的维度。该模型是诊断性的而非规定性的：它支持跨组织比较、揭示配置权衡，并在不强加单一进展路径的情况下将组织定位于共享空间中。更高层级并不固有地更好；目标是在适合组织领域和所选信任范式的维度间实现对齐。这被形式化为对齐假设：有效可信度受智能体权限范围与支持该范围的维度之间匹配度的约束，错位会产生病态风险或不必要的摩擦。我们讨论了实践者如何应用该模型，并概述了实证验证的方向。
英文摘要
The adoption of generative AI in software-intensive systems is proceeding rapidly, but current analytical instruments - principally unidimensional maturity models - compress important configurational variation into a single progressive axis. Drawing on an inductive interview study of eighteen senior practitioners across telecommunications, automotive, defence, aviation, banking, energy, government, and enterprise software services, this paper presents the Trustworthy Autonomy Health Check Model: a structured, multidimensional instrument for characterizing how organizations establish trust in GenAI-assisted software engineering. The model organizes eight empirically grounded dimensions into a system layer (Scope of Agent Authority, Assurance Mechanisms, Data Trustworthiness, Architectural Containment, Traceability & Comprehensibility) and an organizational layer (Governance, Human Oversight Posture, Workforce Capability Sustainability), each on a five-level ordinal scale. A cross-cutting overlay of four trust paradigms - operational, engineering, statistical, and containment-based - captures how trust is established, complementing the dimensions capturing what must be trustworthy. The model is diagnostic rather than prescriptive: it supports cross-organizational comparison, surfaces configurational trade-offs, and locates an organization in a shared space without imposing a single progression path. Higher levels are not inherently better; the goal is alignment across dimensions appropriate to the organization's domain and chosen trust paradigm. This is formalized as the alignment hypothesis: effective trustworthiness is constrained by the fit between the scope of agent authority and the dimensions enabling it, with misalignment producing pathological risk or unnecessary friction. We discuss how practitioners can apply the model and outline directions for empirical validation.
