Skip to content

Beyond Epistemia: Epistemic Schizologia and Large Language Models as Techno-Semiotic Machines

Jul 2026 · arXiv.org · Vol abs/2607.25620 · 0 citations · 28 references
Computer Science

TL;DR

This article accepts that diagnosis but challenges its explanatory framework, to understand a large language model (LLM) as a *techno-semiotic machine* that automates a phase of written semiosis by producing plausible linguistic configurations from the sedimented archive of human writing.

Abstract

Quattrociocchi and colleagues warn that the fluent outputs of large language models may allow linguistic plausibility to substitute for epistemic evaluation, producing the condition they call *Epistemia*: the experience of possessing knowledge without undertaking the practices through which judgment would ordinarily be warranted. This article accepts that diagnosis but challenges its explanatory framework, which compares an embodied, socially situated human knower with an isolated generative model thereby locating epistemic legitimacy in capacities internal to autonomous agents. Drawing on Carlo Sini's philosophy of practices, writing, signs, and technics, we propose instead to understand a large language model (LLM) as a *techno-semiotic machine* that automates a phase of written semiosis by producing plausible linguistic configurations from the sedimented archive of human writing. From this perspective, *Epistemia* is one consequence of a broader phenomenon that we call *epistemic schizologia*: the socio-technical cleavage between signs as linguistically accomplished expressions and signs as moments within socially embedded circuits of interpretation, evidence, criticism, verification, and responsibility. This cleavage is reinforced by *eikotic closure*, through which a plausible continuation is presented with the finality of an epistemic result, and by algorithmic authority and epistemic self-misrecognition. The relevant unit is therefore not the model alone but the complete practice in which generated inscriptions are prompted, interpreted, verified, contested, used, and made consequential. This reframing preserves the distinction between linguistic production and responsible understanding while grounding a design programme centred on inspectable genealogy, contestability, distributed responsibility, epistemic agency, and the evaluation of hybrid human--AIpractices.

View source

Similar papers

#artificial intelligence Preprint Sep 2026

Xeno-Interpretability: Investigating the Alien Minds of LLMs

The aim of interpretability shifts the aim of interpretability from finding human concepts inside models toward discovering and characterizing the representational structures that are native to the models themselves and might affect their behaviour in unpredictable ways.

F. Pierucci, M. B. Syrnikov, M. Prandi et al. · 0 citations
2026

Ifá and Wayang as Posthuman Knowledge Machines: Veridiction, Distributed Agency, and Added Value

This article develops a conceptual-comparative reading of Yorùbá Ifá divination and Javanese wayang kulit as posthuman knowledge machines. It asks how both practices redistribute epistemic agency beyond the human, including what counts as an authoritative speaker, and how they produce veridiction that turns narrative i...

Fitrilya Anjarsari · 0 citations
Open access Sep 2026

What Computation Cannot Be: Linguistic Colonization, Formal Limits, and a Taxonomy of Irreducibly Human Faculties

The article concludes that the burden of proof now lies with those who claim that formal computation can exhaust human understanding, and argues that the simulation–possession distinction provides a principled basis for restoring conceptual clarity to discourse about artificial intelligence.

Iñigo Navarro-Rubio Coello de Portugal, M. Rumayor, G. Génova · 0 citations
Open access Aug 2026

The Magical Power of Words in Large Language Models

It is argued that LLMs represent a fundamental shift in human-technology interaction, one requiring ritualistic linguistic precision rather than technical commands, and that effective prompt construction functions as ritual magic through three essential elements: clear and specific language, contextual framing, and str...

T. Malefyt, Matt Artz · 1 citation
#natural language process... Preprint Sep 2026

From Echo Chambers to Epistemic Monoculture: Large Language Models Present Temporally Contingent Partisan Alignments as Knowledge

Large language models (LLMs) are rapidly becoming an interface between citizens and political information. They are often regarded as"a better Google."While this analogy might work for some instances, it is unintuitively problematic for democratic politics. A search engine retrieves human-authored documents, while a la...

W. Tam · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.