让领域专家掌控AI系统，确保企业级生成式AI可靠可用
The Expert Validation Framework (EVF): Enabling Domain Expert Control in AI Engineering
- 以专家为中心设计四阶段流程，实现对生成式AI的全流程控制
- 通过结构化验证机制提升企业级生成式AI系统的可靠性与可信度
- 适合需要高精度、强监管的金融、医疗等专业领域应用
生成式AI（GenAI）有望重塑知识型工作，但在企业部署中仍受限于缺乏系统性质量保障机制。本文提出专家验证框架（EVF），将领域专家置于构建含生成式AI组件软件的核心位置，通过结构化规范、测试、验证和持续监控流程，使专家能对系统行为保持权威控制。该框架填补了AI能力与组织信任之间的关键鸿沟，建立了一套严谨、由专家驱动的质量保障方法，适用于多样化的生成式AI应用场景。通过涵盖规范制定、系统构建、验证及生产监控的四阶段实施流程，组织可在保障专家监督与质量标准的前提下，有效利用生成式AI能力。
原文摘要 · Abstract (English)
Generative AI (GenAI) systems promise to transform knowledge work by automating a range of tasks, yet their deployment in enterprise settings remains hindered by the lack of systematic quality assurance mechanisms. We present an Expert Validation Framework that places domain experts at the center of building software with GenAI components, enabling them to maintain authoritative control over system behavior through structured specification, testing, validation, and continuous monitoring processes. Our framework addresses the critical gap between AI capabilities and organizational trust by establishing a rigorous, expert-driven methodology for ensuring quality across diverse GenAI applications. Through a four-stage implementation process encompassing specification, system creation, validation, and production monitoring, the framework enables organizations to leverage GenAI capabilities while maintaining expert oversight and quality standards.
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