There is a growing mismatch between how much information modern systems produce and how little attention we pay to the moment when that information is turned into meaning.

The absence of Hazard Semantics in earlier eras was not a mistake. The conditions that demand it - scale, speed, coupling, visibility - are relatively recent.

Hazard Semantics is a distinct interpretive discipline. It is not a rebranding of existing risk, data, or decision frameworks. Clarifying what it is not is essential to understanding what it is.

Hazard Semantics is a newly articulated interpretive discipline concerned with this problem: how meaning forms across multiple domains under complex conditions, and how that meaning can fail even when every underlying signal is technically correct.