From responsibility gaps to meaningful human control: an ethical and regulatory governance framework for intelligent AI systems

Responsible AI beyond compliance: governing everyday use in the public sector

By showing that AI use intensifies rather than replaces human judgment, the study underscores the continued centrality of human responsibility in public decision-making and suggests that effective AI governance requires a shift from restrictive, compliance-focused approaches towards enabling and adaptive strategies.

From AI Alerts to Accountable Decisions: A Governance Framework for Regulatory Compliance

The STAGE framework is proposed as a practical approach to maintaining human judgment and organizational accountability when integrating AI into regulatory compliance and focuses on whether organizations can use AI to identify risks while keeping qualified people responsible for interpreting alerts, making decisions, d...

From automation to ethical authority: governing AI-mediated decision-making in global digital trade

Adaptive, ethical and responsible AI governance for smart cities and nations

Artificial intelligence (AI) is rapidly becoming entrenched across government operations, transforming administrative processes and service delivery, particularly in smart cities and digitally advanced nations. While AI applications such as chatbots, predictive systems, AI of Things (AIoT) devices, robotics, and agenti...

AI Governance Engineering: A Framework for Secure, Explainable, and Trustworthy Enterprise Artificial Intelligence Systems

This paper argues for a transition from AI Governance as Compliance to AI Governance Engineering , a systems-oriented discipline in which governance is embedded throughout the enterprise intelligence lifecycle, enabling enterprise intelligence systems that are secure, explainable, trustworthy, and governable by design.

Human-centric AI governance in the European Union. Accountability, fundamental rights, and institutional resilience in public administration

This Policy and Practice Review concludes that AI-enabled administration remains legitimate only where public authorities retain the capacity to understand, justify, correct, suspend and democratically control the systems they use.