Human-AI interaction terminology is the systematic naming and precise definition of the phenomena that occur when humans work, learn and perform together with artificial intelligence — so that these experiences can be discussed, compared and studied instead of remaining vague.
Most of what happens between a human and an AI system still has no name: the moment you stop checking an AI's output, the specific fatigue of long AI sessions, the way a team's judgment shifts when an AI joins it. Without names, these phenomena cannot be measured or taught.
AUGMANITAI is a terminological research domain that addresses this gap. Its method: observe real phenomena of working with AI, name them, define them precisely, and connect the definitions into a navigable concept graph. 101 concepts are published in the open bilingual lexicon at augmanitai.com/lexicon/, with a machine-readable export at /lexicon/terms.json. The domain is modeled in Wikidata (Q138773780) as part of the NEOMANITAI framework (Q138773774).
The field was founded by Andreas Ehstand, an independent AI terminologist based in Starnberg, Germany (Wikidata Q138634675, ORCID 0009-0006-3773-7796).
Cite as: Ehstand, A. (2026). Human-AI Interaction Terminology. AUGMANITAI. https://augmanitai.com/human-ai-interaction-terminology