AI Assimilationism : The Cultural Flattening of Localities in Generative Models

Ania, Malinowska (2025) AI Assimilationism : The Cultural Flattening of Localities in Generative Models. DISEGNO: A DESIGNKULTÚRA FOLYÓIRATA, 9 (1). pp. 8-25. ISSN 2064-7778

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Abstract

This paper introduces the concept of AI assimilationism to describe a growing tendency in which local and non-Western cultural aesthetics are absorbed into dominant global AI systems that are largely shaped by Western, particularly American, values. Through this process, distinct cultural expressions are rendered visible only after being filtered, standardised, and reformatted to align with prevailing stylistic norms, linguistic hierarchies, and commercial logics. Drawing on cultural theory and histories of mainstreaming minority cultures, the paper argues that AI assimilationism reinforces existing geopolitical and epistemic asymmetries by privileging English-dominated, Western narrative models and marginalizing non-standard languages, aesthetics, and knowledge practices. Focusing on Eastern European cultural production as a case study, it demonstrates how visibility within AI systems often entails the loss of critical specificity, echoing previous examples of cultural mainstreaming, such as the commodification of Black Lives Matter, where political edge and transformative potential were diluted. The paper identifies the emergent risks of digital “ghettoisation,” wherein minority cultures circulate globally but only in narrow, marketable forms. In response, it explores alternative strategies including grassroots artistic interventions, community-based dataset creation, multilingual model development, and demands for epistemic sovereignty. The paper ultimately calls for culturally grounded AI: systems designed not to assimilate but to amplify diverse cultural perspectives, challenging the reproduction of entrenched hierarchies in contemporary technoculture.

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