NEOMANITAI: A Faceted Research Framework for Human-AI Interaction

This conceptual working paper develops NEOMANITAI as a research framework for describing human-AI interaction across digital, embodied and collective settings. It revises an existing umbrella proposal and distinguishes programme names, classification facets, concepts, observations and evidential claims. The edition presents eight ordering conventions, seven descriptive facets, a small typed relation model, three constructed civilian cases and four comparative research questions. The proposed contribution is an inspectable connection between programme navigation, episode descriptions and claim-level provenance. Its usefulness remains to be tested against simpler descriptions and existing approaches. The paper builds on selected historical programme documents and a targeted literature review covering distributed cognition, socio-technical systems, hybrid intelligence, collective intelligence, agents, human-robot interaction, conceptual work and taxonomy development. It reports no new participant data, empirical validation, global novelty finding or established disciplinary status. The constructed cases are explanatory examples. The English paper includes a German abstract. The accompanying JSON contains the conceptual model, examples and recorded literature reading scope. Files: paper PDF, paper TXT, model JSON, README and SHA-256 manifest. This is a new open-access edition. Earlier restricted source records remain separate and their access conditions are unchanged. Drafting and editorial checks were AI-assisted under the author's instruction; external peer review and personal sentence-by-sentence author review are not claimed.