ECA — Endogenously-Constrained AI
ECA — Endogenously-Constrained AI
This document defines Endogenously-Constrained AI (ECA) as the implementation layer of the Crowd-Based Dynamics framework.It translates CBD structural limits into internal constraints governing artificial systems and socio-technical architectures.ECA embeds constraints endogenously, avoiding ex post external control mechanisms.The text grounds ECA in the CBD canonical formula, used as a design grammar rather than a predictive model.It addresses temporal governability, saturation management, mimetic load, and reversibility in artificial agents.Clear boundaries are set, excluding prediction, optimization, or normative enforcement.The document positions ECA as a constrained implementation ensuring structural alignment under scale and complexity.
Endogenously-Constrained AI; Crowd-Based Dynamics; endogenous constraints; temporal governability; saturation management; mimetic dynamics; AI architectures
Endogenously-Constrained AI; Crowd-Based Dynamics; endogenous constraints; temporal governability; saturation management; mimetic dynamics; AI architectures
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