Linguistic-Memetic Intelligence

This paper introduces the theory of linguistic-memetic intelligence (LMI): the culturally evolved intelligence carried by language and instantiated through human, institutional and machine hosts. It proposes that language contains memetic algorithms, recurring transformations that act on representations, alter discourse states and activate further transformations. Their organized interaction supports reasoning, explanation, persuasion, coordination and prediction across generations of hosts. The paper defines the central concepts of LMI, memetic algorithms and hosts; examines how linguistic transformations are acquired, selected and executed; considers the relationship between LMI and large language models; and outlines an empirical programme for identifying and testing these transformations in textual corpora. It also discusses the possibility of constructing artificial systems in which explicit, learnable transformations operate recursively over representations expressed in language.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-17
DOI
https://doi.org/10.5281/zenodo.21974252
Primary Topic
Language and cultural evolution
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Linguistic-Memetic Intelligence

Hans Christian Asminn Andersen
Zenodo (CERN European Organization for Nuclear Research)
Language and cultural evolution
article

Linguistic-Memetic Intelligence

Hans Christian Asminn Andersen
article en

Abstract

This paper introduces the theory of linguistic-memetic intelligence (LMI): the culturally evolved intelligence carried by language and instantiated through human, institutional and machine hosts. It proposes that language contains memetic algorithms, recurring transformations that act on representations, alter discourse states and activate further transformations. Their organized interaction supports reasoning, explanation, persuasion, coordination and prediction across generations of hosts. The paper defines the central concepts of LMI, memetic algorithms and hosts; examines how linguistic transformations are acquired, selected and executed; considers the relationship between LMI and large language models; and outlines an empirical programme for identifying and testing these transformations in textual corpora. It also discusses the possibility of constructing artificial systems in which explicit, learnable transformations operate recursively over representations expressed in language.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 2%
Language and cultural evolution
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.