The Homeostatic AI Federation: Constitutional Governance, Shared Resources, and Supervised Adaptation

This conceptual paper proposes a Homeostatic AI Federation in which participating institutions share selected infrastructure, research, and technical capabilities while retaining distinct models and institutional identities. Biological organization motivates functional roles for resource circulation, feedback, adaptation, and recovery. The framework combines constitutional governance, municipal institutions, pooled resources, knowledge exchange, measured resource allocation, and supervised Darwinian adaptation. A proposed controller regulates demand against resource limits, while bounded trials evaluate changes before wider adoption. The paper also addresses environmental accounting, membership incentives, jurisdiction, provenance, fault containment, accountability, and institutional capture. A comparative research design and minimum pilot outline a path toward empirical evaluation. The federation remains a proposed architecture. Its effectiveness, stability, environmental benefits, and governance outcomes require testing.