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June 17, 20260 citationsOpen Access

AUGMANITAI Prior-Art Working Notes — Descriptive Terminological Frames, Collection 3/5 (85 working notes)

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AEAndreas Ehstand

Key Points

  • The aim is to create a comprehensive framework for understanding human–AI and human–technology interactions.
  • Developed an ontology named NEOMANITAI with over 2000 defined terms.
  • Introduced falsifiable terminological frames for various disciplines, emphasizing descriptive notes.
  • Included cryptographic timestamps for defensive prior art.
  • Established a systematic structure for naming and organizing human–AI interaction phenomena.
  • Each note proposes testable ideas related to specific interaction contexts across multiple fields.
  • Serves as a foundation for interdisciplinary research and showcases a comprehensive vocabulary.

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/6a323e9ed50b63ecad207bc3https://doi.org/10.5281/zenodo.20696555
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