构建AI伦理与合规认证框架，推动欧洲标准下的负责任创新。
Towards a Framework for Supporting the Ethical and Regulatory Certification of AI Systems
- 用语义MLOps实现AI全生命周期管理
- 通过本体驱动的数据溯源保障可追溯性
- 设计RegOps流程落地法规要求，适合政策与AI团队
人工智能已迅速成为欧洲社会与经济的核心技术，但其普及也带来了重大伦理、法律与监管挑战。CERTAIN（人工智能伦理与合规透明认证）项目通过构建综合框架，将监管合规、伦理标准与透明性融入AI系统。本文提出框架核心组件的方法论步骤：(i) 语义机器学习运维（MLOps），实现结构化AI生命周期管理；(ii) 本体驱动的数据血缘追踪，确保可追溯性与责任归属；(iii) 监管运维（RegOps）工作流，将合规要求具体化为可执行流程。通过在多个试点中实施与验证，CERTAIN旨在提升监管合规水平，推动符合欧洲标准的负责任AI创新。
原文摘要 · Abstract (English)
Artificial Intelligence has rapidly become a cornerstone technology, significantly influencing Europe's societal and economic landscapes. However, the proliferation of AI also raises critical ethical, legal, and regulatory challenges. The CERTAIN (Certification for Ethical and Regulatory Transparency in Artificial Intelligence) project addresses these issues by developing a comprehensive framework that integrates regulatory compliance, ethical standards, and transparency into AI systems. In this position paper, we outline the methodological steps for building the core components of this framework. Specifically, we present: (i) semantic Machine Learning Operations (MLOps) for structured AI lifecycle management, (ii) ontology-driven data lineage tracking to ensure traceability and accountability, and (iii) regulatory operations (RegOps) workflows to operationalize compliance requirements. By implementing and validating its solutions across diverse pilots, CERTAIN aims to advance regulatory compliance and to promote responsible AI innovation aligned with European standards.
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