The emergence of generative artificial intelligence requires a reconsideration of established conceptual categories through which human–technology relations have traditionally been described. Terms such as tool, instrument, observer, interaction, agency, partner, and symbiosis carry meanings formed within particular epistemic and philosophical environments, and their transfer into the context of generative AI may alter their conceptual content. This article examines this problem through a dialog…
Read moreThe emergence of generative artificial intelligence requires a reconsideration of established conceptual categories through which human–technology relations have traditionally been described. Terms such as tool, instrument, observer, interaction, agency, partner, and symbiosis carry meanings formed within particular epistemic and philosophical environments, and their transfer into the context of generative AI may alter their conceptual content. This article examines this problem through a dialogue between relational approaches in Western philosophy of physics, Western dialectical thought, and Chinese philosophical traditions, particularly Daoism. Relational Quantum Mechanics (RQM), for example, rejects the assumption of observer-independent physical states and treats physical systems in terms of relations between systems (Rovelli 1996). At the same time, the history of quantum theory demonstrates that dialectical approaches have also played a significant, though non-dominant, role, most notably in David Bohm's engagement with dialectical materialism (Bohm 1957; Gutfreund and Renn 2025). Chinese philosophical traditions provide additional resources for conceptualizing relationality, process, contextuality, and the interdependence of human beings and the wider cosmos (Ames 2011; Song 2021; Wang 2021). Yet neither physical relationality nor traditional human–nature relationality can simply be transferred to the human–AI situation.
The article proposes the concept of a dialectical epistemic environment to describe a specific form of recursive human–generative-AI interaction in which AI-generated conceptual responses can modify the subsequent epistemic state of the human researcher and thereby alter the conditions of the next interaction. This model differs both from the conventional tool relation and from physical interaction between measuring systems. It does not require attributing consciousness, intentionality, or human-like subjectivity to AI. Instead, it identifies a transformation occurring at the level of the epistemic environment itself. The article further introduces conceptual migration as a methodological problem and ontological inflation as the unwarranted elevation of functional or epistemic descriptions into stronger ontological claims.