Clean Word, Clean Function: Language as an Input Regulator in Human–AI Processes

Abstract

Language is commonly evaluated through correctness, politeness, clarity, neutrality, style, and semantic accuracy. These criteria matter, but they do not fully capture what words do inside a living process. This working paper develops the concept of the Clean Word as a functional process regulator. A clean word is not necessarily pleasant, neutral, elegant, or socially acceptable; it is a word or ordered linguistic unit whose effect preserves the relation between trace, image, regulator, transition, and intended product. The paper follows the analysis of corruption as functional capture by examining language as one of the smallest and most powerful interfaces through which a corrupted environment enters human-AI processing. It distinguishes semantic, visual, and functional cleanliness; develops the concepts of initial vector, status preservation, corrupted speech, and clean return; and prepares the transition toward a subsequent analysis of the human, LLM infrastructure, and AWM as a process-regulation architecture for the conditions of the Fourth Industrial Revolution.