Adaptive Governance
Adaptive governance is the framework for governing complex systems in release or reorganization phases, where conservation-phase regulatory mechanisms fail. Its core principles: govern for learning rather than compliance; operate polycentrically across scales rather than within single jurisdictions; maintain diversity of approach rather than converging on a single model; incorporate experiential knowledge alongside expert assessment. Applied to AI, adaptive governance suggests that the EU AI Act, the American executive orders, and emerging frameworks elsewhere — all serious but all conservation-phase instruments applied to a release-phase phenomenon — must be supplemented by institutional arrangements capable of learning as fast as the system they govern.
In the AI Story
Conservation-phase governance works through a characteristic sequence: expert assessment informs regulation, regulation specifies requirements, compliance is monitored, periodic review adjusts. The sequence assumes stable conditions between reviews. The AI transition is changing the system being governed faster than governance cycles can track, producing regulation calibrated for conditions that have already shifted.
The first adaptive principle — govern for learning — changes institutional design from command structure to learning structure, from an institution that knows the right answer to one that acknowledges uncertainty and learns toward effective responses. The Everglades restoration is the paradigmatic case.
The second principle — polycentric governance across scales — addresses the cross-scale cascade of the AI disruption. Local experiments in workforce transition, regional educational innovation, national regulatory frameworks, and international coordination, connected through channels that propagate learning.
The third principle — maintaining diversity of approach — runs counter to the conservation-phase drive toward single best practices. Different jurisdictions experimenting with different models produce a portfolio of natural experiments from which effective approaches can be identified.
The fourth principle — incorporating diverse knowledge — recognizes that experiential knowledge from workers, families, and organizational leaders is unavailable to distant expert panels but essential to governance that responds to lived reality. The silent middle possesses precisely this experiential knowledge; governance must create channels to incorporate it.
Origin
Adaptive governance extends Holling's adaptive management into political and institutional domains; elaborated by Carl Folke, Lance Gunderson, Brian Walker, and the Resilience Alliance network from the early 2000s onward.
Key Ideas
Govern for learning. Treat regulations as hypotheses; monitor effects; adjust systematically.
Polycentric structure. Multiple governance bodies at different scales, connected through coordination and learning channels.
Portfolio of approaches. Maintain jurisdictional diversity; scale up what works.
Incorporate experiential knowledge. Workers, families, and local practitioners possess knowledge unavailable to expert panels.
Appears in the Orange Pill Cycle
Further reading
- Folke et al., 'Adaptive Governance of Social-Ecological Systems' (2005)
- Dietz, Ostrom, Stern, 'The Struggle to Govern the Commons' (2003)
- Lee, Compass and Gyroscope (1993)