Collective Intelligence and Hybrid Reality in a New Journal – Interaction Observations

Abstract

This paper explores how collective intelligence emerges under hybrid reality conditions by examining the interaction between editorial and reader systems during the launch of a new academic journal. It aims to clarify how human and AI reasoning become structurally coupled in scholarly publishing and how this coupling reshapes active participation, reasoning capacity, identifies epistemic blind spots and expands the research frame. The study applies a CyberSystemic interaction-observation framework grounded in second-order cybernetics, interaction theory, and viable system principles. A single bounded interaction of publishing a journal issue is analyzed using a normalized time/zoom (T/Z) observation plane to examine structures, recurrent interactions, and resulting structural changes. The analysis suggests that scholarly publishing can be understood as a hybrid collective in which editorial teams, readers, and AI systems co-produce and co-interpret knowledge. In operational processes, AI-based mediation enhances accessibility and efficiency, but also reinforces mainstream convergence, limiting the identification of blind spots and the expansion of research frames. From this perspective, collective intelligence appears as an emergent potential rather than a realized outcome. Efficient collective intelligence could reduce the need for publishers. The study examines a single interaction episode by a reflexive observer involvement, which may introduce interpretive bias. The paper highlights the need for reflexive governance of human-AI interactions in scholarly communication. It suggests that responsible collective intelligence depends less on automation and more on interaction design, editorial autonomy, and epistemic variety. The paper introduces a CyberSystemic approach that makes hybrid human-AI knowledge processes observable and analyzable in practice.