From Symbol to Meaning: Ontological and Philosophical Reflections on Large Language Models in Information Systems Engineering

TL;DR

This paper explores how Large Language Models fundamentally challenge and reshape the philosophical and semiotic foundations of information systems engineering, urging a re-examination of core conceptual assumptions.

Contribution

It offers a philosophical reflection on LLMs' impact on ontology, epistemology, and semiotics, proposing new perspectives for integrating LLMs into information systems.

Findings

LLMs extend and destabilize classical notions of ontology and signification.

The emergence of LLMs demands rethinking the conceptual foundations of information systems.

LLMs should be viewed as epistemic agents reshaping knowledge processes.

Abstract

The advent of Large Language Models (LLMs) represents a turning point in the theoretical foundations of Information Systems Engineering. Beyond their technical significance, LLMs challenge the ontological, epistemological, and semiotic assumptions that have long structured our understanding of in-formation, representation, and knowledge. This article proposes an integrative reflection on how LLMs reconfigure the relationships among language, meaning, and system design, suggesting that their emergence demands a re-examination of the conceptual foundations of contemporary information systems. Sketching on philosophical traditions from Peirce to Heidegger and Floridi, we investigate how the logic of generative models both extends and destabilises classical notions of ontology and signification. The discussion emphasises the necessity of grounding LLM-based systems in transparent, ethically coherent frameworks that respect the integrity of human-centred knowledge processes. Ultimately, the paper argues that LLMs should be understood not merely as tools for automation but as epistemic agents that reshape the philosophical and semiotic foundations of information systems engineering.