Trust as a Core Primitive of Collective Intelligence

When we talk about ``collective intelligence,'' we often focus on algorithms, incentives, or communication protocols. Yet beneath all of these lies a quieter but more fundamental quantity: \emph{trust}. This post argues, from first principles, that trust is not an optional social add-on but a structural primitive of any system where multiple bounded agents learn, communicate, and act under uncertainty. Getting trust right is therefore central not only to understanding human collectives but also to aligning networks of AI systems for safety.