The regulation of emerging technologies is often conceived as a strategy of catching up, because legislators arrive too late. Yet gathering signals, constructing scenarios and adapting rules to an anticipated future are fundamental tasks for those entrusted with governance, including the governance of rules themselves. The literature on so-called future law has already shown that anticipation means building institutional capabilities rather than predicting outcomes precisely (anticipatory governance). Taking this premise as its starting point, this article proposes to understand regulation as an exploration of the transformations that may occur. The Ruliological Framework for Anticipatory Regulation distinguishes rules, transformations and trajectories, assessing alternatives and possible developments. Within this approach, computational irreducibility is adopted conditionally, not as a demonstrated property of legal systems. The Quantum Europe Strategy provides a case study and further grounds for reflection.
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Figure 1: Illustrative instance of the regulatory state Gt of the European quantum supply chain. Nodes represent actors, infrastructures and capabilities; edges represent funding, supply, access, standardisation and public-demand relationships; the indications within nodes exemplify attributes At . The diagram is a conceptual model, not the outcome of an empirical survey.
Figure 2: Example of a regulatory-state transformation through a procurement rule. Rule r introduces diversification and interoperability requirements. The transition from Gt to Gt+1 represents a possible transformation, not a necessary outcome or an empirically demonstrated causal relationship.
Figure 3: Contextual equivalence between different rules. Starting from the same regulatory state S0 , rule r1 , concerning a pilot line, and rule r2 , concerning procurement, generate different transformations. The transformations may be regarded as equivalent with respect to the property ‘capacity’, while diverging in terms of risk, concentration, demand, access and standardisation. The diagram represents a conceptual model, not the result of a simulation.
Figure 4: The RFAR institutional cycle: observation, generation, filtering through invariants, comparison, selection, monitoring, and revision or termination.