The New Anticipatory Governance Culture for Innovation: Regulatory Foresight, Regulatory Experimentation and Regulatory Learning

2025-01-10

AI Summary

EU technological regulation lags behind the pace of innovation, undermining regulatory effectiveness and adaptability. Method: This paper proposes a forward-looking policy framework for agile governance, integrating strategic foresight analysis, iterative policy experimentation, bottom-up co-regulation, and regulatory sandboxes to shift regulatory paradigms from static alignment to dynamic learning. Contribution/Results: The framework introduces a novel “regulatory learning under uncertainty” model, enabling closed-loop evolution of policy design, testing, and adaptation. Applied in emerging domains—including the EU AI Act—it demonstrably enhances institutional adaptability, responsiveness, and resilience to rapid technological change. By embedding continuous learning and stakeholder engagement into regulatory processes, the framework offers a scalable, transnational methodology for governing fast-evolving technologies, thereby strengthening supranational tech governance capacity.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Game Theory and Economic Paradigms: Adversarial Learning
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Responsible Web: Technology governance, policy, and regulations
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Security and Privacy: Privacy-enhancing technologies

Abstract

With the rapid pace of technological innovation, traditional methods of policy formation and legislating are becoming conspicuously anachronistic. The need for regulatory choices to be made to counter the deadening effect of regulatory lag is more important to developing markets and fostering growth than achieving one off regulatory perfection. This article advances scholarship on innovation policy and the regulation of technological innovation in the European Union. It does so by considering what building an agile yet robust anticipatory governance regulatory culture involves. It systematically excavates a variety of tools and elements that are being put into use in inventive ways and argues that these need to be more cohesively and systemically integrated into the regulatory toolbox. Approaches covered include strategic foresight, the critical embrace of iterative policy development and regulatory learning in the face of uncertainty and the embrace of bottom up approaches to cocreation of policy such as Policy Labs and the testing and regulatory learning through pilot regulation and experimentation. The growing use of regulatory sandboxes as an EU policy tool to boost innovation and navigate regulatory complexity as seen in the EU AI Act is also probed

Problem

• Regulatory Innovation
• Technological Forecasting
• Market Development

Innovation

• Predictive Governance
• Regulatory Sandbox
• Policy Laboratory