Policy-Aware Computing Models for Governing Emerging Technologies

Abstract

Policy-aware computing models embed governance rules, regulatory requirements, and institutional policies directly into the computational systems that operate on emerging technologies, enabling automated compliance enforcement and real-time governance monitoring that manual regulatory processes cannot achieve at the speed and scale of modern technology deployment. Extending the PAECF framework from educational governance (Novak, 2025) to the broader domain of emerging technology governance, this paper proposes the Policy-Aware Computing for Emerging Technology Governance Framework (PACE-TGF), evaluating five policy-aware computing architectures -- policy-as-code automation, AI compliance monitoring, smart contract governance, rights-based constraint systems, and adaptive regulatory sandboxes -- across four emerging technology governance domains: generative AI regulation, autonomous systems certification, biotechnology oversight, and quantum cryptography standardisation. PACE-TGF introduces the Technology Governance Quality Score (TGQS) integrating regulatory compliance coverage, enforcement effectiveness, adaptability to technology evolution, and democratic accountability. Key results: policy-as-code achieves the highest TGQS (0.904) for domains with clear regulatory requirements; adaptive regulatory sandboxes achieve the highest adaptability score (0.960) for rapidly evolving technologies; rights-based constraint systems provide the strongest protection for fundamental rights at the cost of regulatory flexibility. The framework provides policy-aware computing selection guidance for technology governance practitioners and regulators.