Plurification in/of language technology -- The integration of culture in next-generation AI

2026-06-20

AI Summary

This study addresses the limitations of prevailing culturally sensitive approaches in natural language processing (NLP), which often remain confined to surface-level representations and overlook deeper sociocultural contexts and power structures. The paper proposes a sociotechnical framework grounded in pluralistic epistemologies that moves beyond monolithic cultural adaptation paradigms by integrating local knowledge systems into NLP design. Through a five-layer model of technical activity, the authors systematically examine how culture is operationalized in NLP systems and expose critical gaps in current methods concerning governance, power dynamics, and sociocultural embeddedness. This approach reframes culture from a static object of representation to a dynamic, actionable construct, thereby advancing more reflexive and inclusive forms of cultural alignment in NLP.

Abstract

The paper explores how "culture" can be operationalised in Natural Language Processing (NLP) and what this reveals about the possibilities and limits of considering a plurality of cultural backgrounds in technological design. It proposes that cultural alignment cannot be achieved only by adding more examples of "other cultures", rather it requires plural epistemologies: allowing multiple, locally grounded ways of knowing. To analyze how this plurality of knowing can be addressed in NLP, the paper uses a socio-technical model of language technology (LT) design, the five layers of technological activity model, for collecting and systematizing approaches to culture in NLP. The analysis shows that while NLP research has made progress toward more culturally sensitive systems, many approaches remain partial, addressing "culture" primarily at the level of output or representation while leaving deeper questions of power, governance, and social context unresolved. The paper concludes that operationalising culture requires much more than technical adaptation; it suggests a reflexive and plural socio-technical approach that navigates potentials and limits of computational formalisation for accounting multiple linguistic and socio-cultural backgrounds.

Problem

• culture
• plurality
• natural language processing
• socio-technical
• epistemologies

Innovation

• plural epistemologies
• cultural alignment
• socio-technical model
• natural language processing
• computational formalisation