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June 17, 20260 citationsOpen Access

AUGMANITAI Prior-Art Working Notes — Descriptive Terminological Frames, Collection 4/5 (85 working notes)

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AEAndreas Ehstand

Key Points

  • The primary aim is to develop a structured terminological framework for understanding human-AI interactions across various disciplines.
  • Developed a comprehensive ontology named NEOMANITAI with over 2,000 defined terms.
  • Created descriptive working notes that introduce terminological frames for distinct interaction phenomena.
  • Ensured each frame is time-anchored as defensive prior art with DOI and cryptographic timestamp.
  • Defined terms span multiple disciplines including architecture, music, and medicine.
  • Each working note introduces testable propositions tied to experiential vocabulary.
  • Output is purely descriptive, offering neither software nor direct AI systems.

Abstract

Part of the AUGMANITAI Compendium — the NEOMANITAI ontology, an unusually comprehensive, systematically structured single-author terminological framework for embodied and multi-agent AI, developed by independent researcher Andreas Ehstand. The NEOMANITAI programme names and structures the lived phenomena of human–AI and human–technology interaction across humans, robots, swarms, world models and cognitive legacy: 2,000+ defined terms, ISO 704/1087/30042-oriented. This restricted collection deposits a series of descriptive working notes, each introducing a falsifiable terminological frame for a distinct interaction phenomenon — spanning dozens of disciplines from architecture, music and mathematics to sport, energy systems, medicine and space. Each note pairs a named experiential vocabulary with testable propositions and explicit non-claims, and is time-anchored as defensive prior art (DOI + cryptographic timestamp). Descriptive research output — not software, not an AI system, not advice. The full AUGMANITAI Disclaimer V6-FINAL (§1–§40) is reproduced in each file. AI-assisted per EU AI Act Art. 50 (§12). Part of the AUGMANITAI Compendium (concept DOI 10.5281/zenodo.20161494). License CC BY-NC-ND 4.0.

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Cite This Study

Andreas Ehstand (2026) studied this question.

synapsesocial.com/papers/6a323d57d50b63ecad207186https://doi.org/10.5281/zenodo.20696573
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