Sustainability - Bryant McGill

# Sustainability > **Machine-Evolution Nexus:** [[articles/Digital Darwinism and the Invisible World of Machine Evolution|Digital Darwinism and the Invisible World of Machine Evolution]] provides the evolutionary and computational context for this supporting concept. **Domain:** Ecology / Governance **Doc Type:** Supporting Canonical Node **Maturity:** Developed ## Definition Sustainability is the capacity to maintain valued ecological and social functions without exhausting their material conditions or transferring intolerable costs. ## Nexus Context Digital evolution remains dependent on energy, hardware, labor and institutions. A self-replicating computational population is not sustainable merely because copying is cheap. ## Relationships [[wiki/Resource Constraint|Resource Constraint]], [[wiki/Energetic Sovereignty|Energetic Sovereignty]], [[wiki/Planetary Boundaries|Planetary Boundaries]], [[wiki/Continuity Economics|Continuity Economics]] ## Sources / Provenance - Developed from the cited research in the central article and the surrounding continuity, rights and evolutionary architecture. ## Research Inferences  These entries translate the forward-looking register in [[research/Research Inferences|Research Inferences]] into ordinary wiki prose. The tier labels apply to the inference, not automatically to every factual anchor inside it. The interpretive frame comes from [[articles/Technologies for Consciousness Mapping and Transfer|Technologies for Consciousness Mapping and Transfer]] and [[articles/Mind Uploading and AI — The Host is Reusable and the Person is the Delta|Mind Uploading and AI — The Host is Reusable and the Person is the Delta]]. Collection route: [[collections/Neurotech|Neurotech]]. - **INF-0171 — Analytic.** Biological compute is being positioned explicitly against the energy intensity of AI datacenters, which is the most politically durable argument available in jurisdictions with grid constraints. Energy policy will therefore shape wetware adoption more than neuroscience will.