Gianni Jacucci, University of Trento, Italy

Current AI models, particularly large language models (LLMs), are predominantly grounded in positivist epistemology, treating knowledge as an external, objective entity derived from statistical patterns in data. However, this paradigm fails to capture "facts-in-the-conscience", the subjective, meaning-laden experiences central to human sciences. In contrast, phenomenology hermeneutics and constructivism, as fostered by socio-technical research (16), provide a more fitting foundation for AI development, recognizing knowledge as an intentional, co-constructed process shaped by human interaction and community consensus. Phenomenology highlights the lived experience and intentionality necessary for meaning-making, while constructivism emphasizes the social negotiation of knowledge within communities of practice. This paper argues for an AI paradigm shift integrating second-order cybernetics, enabling recursive interaction between AI and human cognition. Such a shift would make AI not merely a tool for knowledge retrieval but a co-participant in epistemic evolution, supporting more trustworthy, context-sensitive, and meaning-aware AI systems within socio-technical frameworks.

AI epistemology, Large Language Models(LLMs), Consensus Domain, Human-AI Interaction, Structural Coupling