Objectivity, subjectivity and generative AI:

On the paradox of (paramedic) scientific communication and cybernetic truth

Abstract

Background and Research Question: Generative Artificial Intelligence (gAI) is transforming the epistemic core of scientific work. Modernity understood science primarily as the production of verifiable knowledge, stabilized through methodological objectification and linear publication logics. With gAI, however, new forms of semantic surplus and fragmented resonance spaces emerge, placing the classical concept of truth and the attribution of authorship under increasing pressure. This article investigates how the concept of truth changes when science moves beyond mere knowledge accumulation and increasingly becomes a movement of questioning, while gAI as a new “co-communicator” renders subjectivity and authorship in science more visible.

Methodology: A theoretical and systematic analysis drawing on epistemology (Kant, Weizsäcker), systems theory (Luhmann, Baecker), and current debates on gAI, in order to develop a conceptual perspective on truth as a cybernetic process interlinking experience, consciousness, and communication.

Results: The analysis shows that the classical truth code (“true/false”) is increasingly under pressure. Innovation and resonance are emerging as new selection values within scientific communication. Science is thus appearing less as a system of secured knowledge stocks and more as a dynamic movement of inquiry and questioning, productively engaging with the inevitable semantic surplus of its own communication instead of merely filtering it through disciplinary boundaries.

At the same time, it becomes evident that subjectivity, despite its methodological exclusion, remains an indispensable precondition for knowledge. This paradoxical structure is intensified by the rise of generative AI, which acts as a co-communicator with no clear epistemic status and no unequivocal attribution of authorship or intentionality. Attempts to integrate gAI into the established mode of objectivity through comprehensive documentation requirements or an expansion of control mechanisms prove illusory: gAI resists total control and—much like the researcher’s subjectivity—is pushed into the zone of silence and structural exclusion that scientific communication requires in order to sustain its claim to objectivity.

Thus, gAI does not represent a mere methodological advance; it amplifies the media-theoretical paradox of science: knowledge depends on conditions it cannot openly address and now extends this blind spot to include a technological agent that cannot be fully regulated within the traditional system of objectivity.

Discussion: The “next science” requires a concept of truth that no longer relies on absolute objectivity but on emergent coherence, resonance, and reflexive subjectivity. gAI reveals that knowledge production arises not solely from data and method but from an open process of questioning. The central challenge is to maintain this openness without falling into arbitrariness.

Conclusion: Science must be redefined as a cybernetic practice of truth-seeking: less a static repository of knowledge, more a reflexive movement of inquiry. gAI acts here not merely as a tool but as a co-communicator, deepening the epistemic paradox of subjectivity and objectivity and opening the path toward a question-driven, resonance-sensitive science.