The Stewardship Principle: Adaptive Capacity, Learning, and the Conditions for Durable Intelligence

The Stewardship Principle proposes that adaptive capacity—not optimisation—is the invariant property linking durable intelligent systems across biological, institutional, and artificial domains. It argues that learning is the principal process through which adaptive capacity is preserved, and that reality-testing functions as a civilisational commons upon which institutional learning and self-correction depend. From this structure, stewardship follows not merely as an ethical preference but as a necessary property of durable intelligence. The paper draws together insights from cybernetics, resilience theory, evolutionary biology, institutional economics, commons governance, and artificial intelligence safety. It presents a foundational axiom, a proposed First Law of Stewardship, possible architectural implementations, candidate indicators, historical cases, and explicit conditions under which the central hypothesis should be revised or rejected. This document is released as Version 1.0 of an open research programme. It is intended to be criticised, tested, extended, and—where necessary—refuted.