CONCEPT
Adaptive Efficiency
North's distinction between static optimization under current conditions and the capacity of an institutional framework to evolve as conditions change — the property that determines whether rules designed for today's AI become traps when tomorrow's arrives.
North distinguished between two forms of institutional efficiency. Allocative efficiency refers to the static optimization of resource allocation given current conditions — the standard efficiency measure of neoclassical economics. Adaptive efficiency refers to the capacity of an institutional framework to evolve in response to changing conditions. A framework that is allocatively efficient at a given moment may be adaptively inefficient if it lacks mechanisms for self-correction when conditions change. The AI transition demands adaptive efficiency above all, because the technology is evolving faster than any specific institutional arrangement can anticipate. Formal rules specifying how AI must be used will become obsolete before the ink is dry. What is needed instead are institutional mechanisms enabling continuous adaptation — regulatory sandboxes that permit experimentation, sunset provisions that force periodic review, feedback mechanisms that transmit information about institutional performance to the actors responsible for institutional maintenance.
In The You On AI Field Guide
The European Union's AI Act represents one approach to