regulris

Regulris is a theoretical framework used in discussions of regulatory design that emphasizes adaptive, rule-based governance for complex, dynamic environments. It envisions regulatory systems as modular, interacting components that adjust policies in response to feedback rather than relying on fixed rules alone. The concept is used in academic and policy discourse to address rapid technological change and systemic risk.

Its name is a neologism combining "regula" (rule) with a suffix suggesting system-level integration. It emerged in the late 2010s and early 2020s in debates on AI governance, climate policy, and financial regulation. While not universally defined, Regulris shares roots with cybernetic and systems-theory approaches to governance.

Key principles include modularity, continuous feedback, adaptive thresholds, data-driven oversight, and layered governance. Regulris advocates near-real-time monitoring, risk-based triage of interventions, and the ability to scale or roll back rules as conditions change. It emphasizes transparency of data and decision rules to maintain legitimacy.

Operationally, Regulris envisions regulatory modules that monitor specific risk vectors, coordinate through central governance, and employ automated triggers while preserving human oversight for high-stakes decisions. It supports sandbox experiments and phased rule changes to test regulatory impact before wide deployment.

Applications discussed include AI safety regulation, financial-market resilience, environmental policy, and infrastructure security. Proponents argue Regulris can reduce lag between risk emergence and policy response while avoiding over-correction; critics warn of complexity, opacity, uneven implementation, and potential circumvention through loopholes or gaming.

See also: adaptive regulation, regulatory sandbox, cybernetics, systems theory, governance.