arXiv:2606.13039cs.CYcs.AI2026-06

研究英国央地政府在教育领域推行AI时的伦理困境与实践断层。

Fault Lines: Navigating Ethics and Responsible AI Where National Policy Meets Local Practice in Public Sector Transformation

  • 通过17次访谈分析央地协同中的责任落地难题。
  • 发现五类核心障碍:数据滥用、市场失衡、人力不足等。
  • 适合政策制定者与公共部门管理者阅读。

面对严峻财政压力,英国政府积极推动人工智能以转型公共服务,但如何将国家战略转化为负责任的本地实践仍不清晰。尽管政策由中央制定,实际服务交付却由地方机构负责,而当前以AI为核心的公共服务变革正在暴露中央与地方之间知识与实践的断裂。本文以特殊教育需求(SEND)这一高风险领域为案例,通过对17位政策制定者、一线从业者及第三方组织人员的半结构化访谈,开展主题分析,识别出五大相互关联的挑战:非正式使用AI带来的数据隐私风险、政府与市场在AI供给中的不对称关系、人力资源准备不足、缺乏标准化定义与评估指标,以及人类责任机制缺失。受访者针对每项问题提出具体应对建议,如强化数据保护框架、重塑政企合作关系、提升人员能力。研究揭示,在涉及弱势儿童与家庭的高风险决策中,问责、公平与人工监督的张力尤为突出,凸显原则导向监管的局限性。本文主张,实现负责任的公共部门AI需同时推动国家政策调整和地方机构在能力建设、价值体系与治理机制上的结构性改革。

原文摘要 · Abstract (English)

The UK government has adopted a pro-AI stance to help transform public service delivery in the face of severe financial pressures, but the path to translate this vision into responsible AI practice remains ill-defined. While UK policy is often set at the national level, local authorities are responsible for most public service delivery, and the rapid advance of AI-first narratives in the public sector is exposing fault lines in knowledge and practice at this national-local interface. This paper examines how responsible AI is interpreted and implemented at the interface between the UK's central government and local authorities, taking the high-stakes area of Special Educational Needs and Disabilities (SEND) as a case study. We present a thematic analysis of 17 semi-structured interviews with policymakers, practitioners, and third-sector professionals to identify barriers and enabling conditions for responsible AI where national policy meets local practice. We identify five interconnected challenges facing local authorities: shadow usage of AI and data privacy risks, market-government asymmetry in AI provision, insufficient workforce readiness, a lack of standardised definitions and measurements, and gaps in human accountability. For each, participants proposed actionable steps, from strengthening data protection frameworks and rebalancing the market-government relationship to enhancing workforce capacity. Our examination of SEND brings these challenges into sharper focus, showing how high-stakes decisions affecting vulnerable children and families intensify tensions around accountability, fairness, and human oversight, exposing the limits of a principle-based regulatory approach. We argue that responsible public sector AI requires both national policy adjustments and structural reforms to institutional capacity, values, and governance mechanisms at the local level.

AI伦理公共政策央地协同教育科技

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