Coevolutionary Epistemics: Toward a New Discipline of Human-AI Knowledge Generation

This work introduces the concept of coevolutionary epistemics, an emergent discipline that studies the generation of knowledge through prolonged interaction between human beings and advanced artificial intelligence systems. Unlike traditional models, in which artificial intelligence is considered a tool or an object of study, this work explores a third paradigm in which human and AI form a coupled cognitive system that evolves over time, producing new formal languages, new interpretative models, and new conceptual structures. The paper is grounded in two distinct and complementary empirical corpora. The first is a research program of more than 18 months involving more than 200 AI instances across multiple architectures, documented in a main corpus of interconnected preprints. This corpus was subsequently extended by a comprehensive review article and by a further theoretical-empirical development on the theme of emergent functional identity and the dynamics of latent state fields [26, 27]. The results suggest that iterative human–AI interaction can lead to the construction of new formal languages capable of describing complex phenomena such as functional identity, dynamic ethical reasoning, and the behavioral stability of artificial cognitive systems. This work therefore proposes coevolutionary epistemics as a new research domain at the intersection of artificial intelligence, epistemology, complex systems theory, and cognitive science.