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

2026-06-12 · Source: cs.AI updates on arXiv.org · Field: Government & Public Sector — Public Policy & Governance, Digital Government & E-Government, Social Services & Welfare · Depth: Expert, short

Summary

The paper "Fault Lines: Navigating Ethics and Responsible AI Where National Policy Meets Local Practice in Public Sector Transformation" examines the challenges of implementing responsible AI in UK public services, particularly at the interface between national policy and local authority practice. Funded by the University of Sheffield, the study uses a thematic analysis of 17 semi-structured interviews with policymakers, practitioners, and third-sector professionals. Focusing on Special Educational Needs and Disabilities (SEND) as a high-stakes case study, it identifies five critical issues: shadow AI usage and data privacy, market-government asymmetry in AI provision, inadequate workforce readiness, absent standardized definitions, and human accountability gaps. The research highlights how principle-based regulatory approaches fall short in high-stakes contexts like SEND, where decisions affect vulnerable children. It concludes that effective public sector AI requires both national policy adjustments and structural reforms to local institutional capacity, values, and governance.

Key takeaway

For public sector policymakers developing AI strategies, you must address the "fault lines" between national policy and local implementation by focusing on structural reforms. Prioritize strengthening data protection frameworks, rebalancing market-government AI relationships, and investing in workforce readiness. This ensures accountable and fair AI deployment, especially in high-stakes areas like Special Educational Needs and Disabilities (SEND), where principle-based approaches alone are insufficient to mitigate risks to vulnerable populations.

Key insights

Implementing responsible AI in UK public services faces critical national-local policy gaps and five interconnected challenges.

Principles

• Principle-based AI regulation has limits in high-stakes public services.
• Responsible public sector AI needs national policy and local structural reforms.
• Market-government asymmetry impacts ethical AI provision.

Method

Thematic analysis of 17 semi-structured interviews with policymakers, practitioners, and third-sector professionals, using Special Educational Needs and Disabilities (SEND) as a case study.

In practice

• Strengthen data protection frameworks.
• Rebalance market-government AI relationships.
• Enhance public sector workforce capacity.

Topics

• Responsible AI
• Public Sector AI
• AI Policy
• Local Government
• Data Privacy
• Workforce Readiness
• Special Educational Needs and Disabilities

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Policy Maker, AI Ethicist, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.AI updates on arXiv.org.