提出四层架构,系统整合智能政府的技术与治理逻辑。
The Algorithmic State Architecture (ASA): An Integrated Framework for AI-Enabled Government
- 构建数字基建、数据政策、算法治理与政务科技四层联动框架
- 实证分析四国案例,揭示各层协同对服务落地的关键作用
- 适合研究数字政府或推动智能治理的政策制定者参考
随着人工智能重塑公共部门运作,各国在将技术创新整合为有效服务体系方面面临挑战。本文提出算法型国家架构(ASA),一个包含数字公共基础设施、数据驱动政策、算法化政府/治理以及政务科技的四层集成框架,阐明其在智能国家中的相互依存关系与反馈机制。不同于将这些领域视为并行发展的传统视角,ASA强调各层间的动态耦合。通过对爱沙尼亚、新加坡、印度和英国的比较分析,研究发现基础数字设施支撑系统性数据采集,进而赋能算法决策,最终实现面向用户的服务输出。成功实施需各层均衡发展,并重点关注层间整合机制。该框架在理论上弥合了数字政府研究中分散领域的鸿沟,识别出影响实施成效的关键依赖关系,并为评估智能政府系统的成熟度与发展路径提供结构化方法。
原文摘要 · Abstract (English)
As artificial intelligence transforms public sector operations, governments struggle to integrate technological innovations into coherent systems for effective service delivery. This paper introduces the Algorithmic State Architecture (ASA), a novel four-layer framework conceptualising how Digital Public Infrastructure, Data-for-Policy, Algorithmic Government/Governance, and GovTech interact as an integrated system in AI-enabled states. Unlike approaches that treat these as parallel developments, ASA positions them as interdependent layers with specific enabling relationships and feedback mechanisms. Through comparative analysis of implementations in Estonia, Singapore, India, and the UK, we demonstrate how foundational digital infrastructure enables systematic data collection, which powers algorithmic decision-making processes, ultimately manifesting in user-facing services. Our analysis reveals that successful implementations require balanced development across all layers, with particular attention to integration mechanisms between them. The framework contributes to both theory and practice by bridging previously disconnected domains of digital government research, identifying critical dependencies that influence implementation success, and providing a structured approach for analysing the maturity and development pathways of AI-enabled government systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。