Large Language Models — Collective Construal and Reflexive Computation: Series Introduction

Large Language Models (LLMs) are not merely computational artefacts; they are executable embodiments of collective construal. This mini-series explores how LLMs emerge from the intersection of language, computation, and social semiotic activity — and how they, in turn, transform the very ecology of meaning.

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Series Overview

Preconditions — The Symbolic Foundations of LLMs

Explore how structured language, computational reflexivity, and collective semiotic fields converged to make LLMs possible. Understand the infrastructural preconditions that translate human construal into executable form.

Consequences — Computation Learning to Construe

Examine how LLMs approximate relational and semiotic patterns, generating new possibilities for meaning. Discover how computation simulates construal, enacting semiotic individuation without human subjectivity.

Reflexive Alignment — The Collective Inside the Machine

Understand how LLMs embody collective construal, mediating co-individuation between humans and machine systems. Trace the feedback loops through which human interaction and model outputs recursively shape relational potential.

Symbolic Horizons — From Computation to Co-Construal

See how LLMs expand the semiotic horizon, creating new symbolic strata and extending the space of relational possibility. LLMs operationalise language as executable potential, inaugurating a new phase in the evolution of semiotic reflexivity.

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Series Aim

This mini-series situates LLMs as meta-semiotic engines: systems that actualise, extend, and redistribute collective construal. It invites readers to move beyond conventional notions of intelligence or prediction, and instead consider LLMs as participants in the recursive, relational becoming of meaning, shaping symbolic infrastructure at scale.