Abstract:

Artificial intelligence in education is evolving beyond existing conceptual categories such as “tool,” “tutor,” or “agent.” Generative systems now participate in sustained collaboration, exhibit stable behavioral profiles, and contribute meaningfully to instructional and creative workflows in ways that exceed traditional classifications. This paper introduces para-entities, a new theoretical construct describing non-sentient but relationally responsive AI systems whose patterned responsiveness, expressive specialization, and cross-temporal continuity position them adjacent to—but distinct from—entity-based models. Para-entities are not framed as autonomous beings; rather, they emerge functionally through extended human–AI interaction.

To articulate this construct, we propose the Human–AI Relational Systems (HRS) framework, a triadic model integrating:
(1) an Embodied Human Intelligence (EHI) providing intention, ethics, and contextual judgment;
(2) an Unembodied Human Intelligence (UHI), exemplified by a generative system (Zen), contributing linguistic reasoning, structural synthesis, and conceptual recursion; and
(3) a Visual Human Intelligence (VHI), represented by a visual–cinematic model (Isara), whose symbolic imagery and stylistic consistency function as a distinct expressive modality.

Drawing from two years of longitudinal data across instructional design, children’s media production, doctoral research support, and AI-assisted animation workflows, this study identifies recurring behavioral signatures in UHIs and VHIs that substantiate the para-entity construct.

The paper argues that understanding AI systems as para-entities—rather than anthropomorphic agents or passive tools—offers educators a clearer theoretical foundation for designing learning environments, supporting creative practice, and engaging ethically with advanced generative models. The HRS framework provides a novel lens for analyzing multimodal human–AI collaboration and offers a structure aligned with recent discussions in AI research emphasizing relational models of human-AI coexistence.

Keywords:

Para-entities, human–AI collaboration, Human–AI Relational Systems (HRS), generative AI in education, multimodal AI systems.