提出SCOR框架，助多主体数字生态实现负责任的AI创新。
SCOR: A Framework for Responsible AI Innovation in Digital Ecosystems
- 构建四支柱框架：共担伦理章程、协同设计、持续监督与动态合规。
- 提供轻量模块与深度审计系统，适配不同规模组织需求。
- 适用于医疗、金融、智慧城市场景，兼顾量化指标与信任评估。
AI驱动的数字生态系统涵盖技术公司、监管机构、加速器和民间社会等多元利益相关方，但常缺乏连贯的伦理治理。本文提出一个四支柱框架（SCOR），在多主体网络中嵌入问责、公平与包容性。通过设计科学方法，构建共享伦理宪章（S）、结构化协同设计与利益相关方参与协议（C）、持续监督与学习机制（O），以及自适应监管对齐策略（R）。各组件提供实用指南，从资源有限初创企业的轻量模块到大型联盟的深度审计系统。通过医疗、金融和智慧城市的案例分析，展示该框架如何协调组织文化、领导激励与跨司法管辖区合规。混合方法的关键绩效指标设计确保定量目标与用户信任及文化变革的定性评估相辅相成。通过将伦理原则与可扩展的运营结构结合，本文为复杂数字生态中的负责任AI创新提供了可复制路径。
原文摘要 · Abstract (English)
AI-driven digital ecosystems span diverse stakeholders including technology firms, regulators, accelerators and civil society, yet often lack cohesive ethical governance. This paper proposes a four-pillar framework (SCOR) to embed accountability, fairness, and inclusivity across such multi-actor networks. Leveraging a design science approach, we develop a Shared Ethical Charter(S), structured Co-Design and Stakeholder Engagement protocols(C), a system of Continuous Oversight and Learning(O), and Adaptive Regulatory Alignment strategies(R). Each component includes practical guidance, from lite modules for resource-constrained start-ups to in-depth auditing systems for larger consortia. Through illustrative vignettes in healthcare, finance, and smart city contexts, we demonstrate how the framework can harmonize organizational culture, leadership incentives, and cross-jurisdictional compliance. Our mixed-method KPI design further ensures that quantitative targets are complemented by qualitative assessments of user trust and cultural change. By uniting ethical principles with scalable operational structures, this paper offers a replicable pathway toward responsible AI innovation in complex digital ecosystems.
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