HOMOGENISED HERITAGE: AI AND CENTRAL EUROPE
Editors: Zsolt Gyenge, Olivér Horváth (Managing Editor), Márton Szentpéteri. Guest editor: Brigitta Iványi-Bitter. Founding Editor: Heni Fiáth (2014–2018)
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Table of Contents
introduction
Brigitta Iványi-Bitter: Visibility under AI Mediation
research papers
Ania Malinowska: AI Assimilationism: The Cultural Flattening of Localities in Generative Models
Michał Krzykawski: Beyond Computational Illusion: Futures Worth Wanting
for Artistic Practices and Technical Cultures
Brigitta Iványi-Bitter, Tibor Bacsi, and Szilárd Szakács: Epistemic Cultural Flattening in Generative Visual AI: Benchmarking Hungarian Heritage and Designing a V4 Path Toward Culturally Aware Text-to-Video
Kateřina Marková: Against Collective Vulnerability: Understanding Cultural Alignment in LLMs (Not Only) in Central Europe and Calling Design Research to Help
Anna Keszeg: The Paprika-Effect. Central and Eastern Europe as a Noisy Label in AI-Generated Images
Jiří Philippe Janda: North Bohemia as a Low-Resource Visual Context: Everyday Heritage, Uneven Visibility, and Synthetic Aesthetics
David Kořínek: The Liminality of Generative Creation: The Artistic Process Between Intuition and Algorithm
Albín Kuchta & Alžbeta Kuchtová: Virtual Spaces: Tools of Poetic Resistance or Censorship Devices?
about the authors
Brigitta Iványi-Bitter: Visibility under AI Mediation
Disegno 2025/1, page range: 4-7.
https://doi.org/10.21096/disegno_2025_1bib
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Ania Malinowska: AI Assimilationism: The Cultural Flattening of Localities in Generative Models
Disegno 2025/1, page range: 8-25.
https://doi.org/10.21096/disegno_2025_1am
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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Michał Krzykawski: Beyond Computational Illusion: Futures Worth Wanting for Artistic Practices and Technical Cultures
Disegno 2025/1, page range: 26-38.
https://doi.org/10.21096/disegno_2025_1mk
Artists and cultural theorists, although they use different means, share the task of problematizing culture. The urgent task now is to critically examine the ways we use AI text-to-image generators and create space for reflection about engaging with these systems. I approach this through what I term the cultural logic of computational capitalism, drawing on Fredric Jameson and Bernard Stiegler. The paper addresses how arts and humanities can help overcome this logic and transform AI’s visual culture itself. Such an inquiry is essential given that AI text-to-image generators not only disrupt traditional art production but also concentrate creative power in the hands of a few dominant platforms. While these concerns are global, they require specific regional responses. Focusing on East-Central European countries, I argue that the underrepresentation of their visual cultures in AI models stems from their semi-peripheral status within global technological and economic systems. Rather than simply feeding existing AI models with better regional training data, I propose supporting dissident artistic practices that promote regional digital and digitally sustainable cultures.
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Brigitta Iványi-Bitter, Tibor Bacsi, and Szilárd Szakács: Epistemic Cultural Flattening in Generative Visual AI: Benchmarking Hungarian Heritage and Designing a V4 Path Toward Culturally Aware Text-to-Video
Disegno 2025/1, page range: 40-67.
https://doi.org/10.21096/disegno_2025_bi-btbszsz
Generative image systems increasingly shape how culture becomes visible in design workflows and heritage interpretation. Their outputs often achieve technical plausibility while offering limited support for validating cultural provenance, shaping how synthetic images circulate as cultural references. This article introduces Epistemic Cultural Flattening (ECF) and an Epistemic Interpretive Framework (EIF) to distinguish structural performance from epistemic readability and to describe reductions of culture-specific legibility under globally dominant visual templates. The study operationalizes EIF through a cultural fidelity benchmark rating generated images by cultural fit, stylistic accuracy, and technical quality. It uses a Hungarian heritage benchmark set within a cross-cultural comparative corpus and compares outputs from four diffusion-based generators. The article proposes an ECF failure-mode typology that makes cultural flattening visually legible. It also outlines a V4-oriented workflow for culturally aware text-to-video, integrating GLAM sourcing, multilingual metadata, controlled model adaptation, and expert review for low-resource cultures in Central Europe.
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Kateřina Marková: Against Collective Vulnerability: Understanding Cultural Alignment in LLMs (Not Only) in Central Europe and Calling Design Research to Help
Disegno 2025/1, page range: 68-89.
https://doi.org/10.21096/disegno_2025_1km
Large language models promise ef ficiency and personalisation, yet they also carry Global North values that may conf lict with regional principles and distort human mental models. When profit-driven technological development meets personalisation, the risk of f lattening cultural diversity into a computational mean grows, which can be interpreted in terms of collective vulnerability. I argue that this ef fect is not unique to Central Europe but is shared across all linguistic and cultural communities, albeit for slightly dif ferent reasons. Using a Czech-language experiment I explore how design research practices can help us understand the phenomenon known as epistemic cultural f lattening. Finally, I chart a possible path to improving cultural alignment as one of the elements that can help us toward better personalised AI tools.
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Anna Keszeg: The Paprika-Effect. Central and Eastern Europe as a Noisy Label in AI-Generated Images
Disegno 2025/1, page range: 90-107.
https://doi.org/10.21096/disegno_2025_1ak
This article examines how AI-generated images reproduce geopolitical imaginaries of Central and Eastern Europe (CEE) through a visual analysis of images generated using Midjourney. Drawing on popular geopolitics as a theoretical framework, the study situates AI image generation within a long-standing transglobal media environment in which visual culture plays a key role in shaping geopolitical knowledge and spatial hierarchies. Popular geopolitics foregrounds the power of everyday visual representations in producing meaning beyond formal discourse, a dynamic intensified by generative AI systems. Methodologically, the study analyses a dataset of eighty AI-generated images across twenty countries, using standardised prompts varying by gender and dress (folk costume versus contemporary clothing). The analysis focuses on culturally coded visual markers such as facial features, stylisation, and their relation to dress. The article conceptualises the observed pattern as the “paprika-effect”: a form of epistemic cultural flattening in which complex regional identities are reduced to exaggerated, globally recognisable, and unevenly documented visual tropes. The findings suggest that generative AI systems reproduce not cultural accuracy, but the contradictions inherent in transglobal geopolitical imaginaries. Rather than offering a fully systematic or generalisable account of AI image generation, this study adopts an exploratory approach. The analysis is intended to function as a hypothesis-generating intervention, identifying patterns that raise broader questions about the relationship between generative AI and geopolitical imaginaries, and it does not provide definitive empirical conclusions.
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Jiří Philippe Janda: North Bohemia as a Low-Resource Visual Context: Everyday Heritage, Uneven Visibility, and Synthetic Aesthetics
Disegno 2025/1, page range: 108-31.
https://doi.org/10.21096/disegno_2025_1jpj
Generative AI images are not neutral depictions of place: they translate regions through uneven training data and model priors. Using North Bohemia (Czech Republic) in an “ordinary documentary” 1990s register, this study tests 13 prompts across four models and maps drif t with TDS (8 variables, 0–2). Findings indicate structured drif t: vernacular loss, infrastructural “cleaning,” and stylistic takeover that smooths local memory into globally legible templates—raising questions about everyday heritage visibility in the V4/CEE context.
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David Kořínek: The Liminality of Generative Creation: The Artistic Process Between Intuition and Algorithm
Disegno 2025/1, page range 132-46.
https://doi.org/10.21096/disegno_2025_1dk
This study theorises artistic collaboration with generative artificial intelligence through the concept of generative liminality, understood as a transitional and unstable zone in which human intention, cultural memory, and algorithmic inference enter into negotiation. Grounded in a case study of Rafani’s exhibition Everyone Has the Right to Everything(Gallery 8smička, 2025), the analysis examines how AI-assisted creation operates within a small-language, post-socialist context shaped by ideological ambivalence, satire, and distrust of universalist promises. Developed in Czech and structured around locally specific political references, the project exposed the frictions that emerge when globally trained AI models engage regional realities. Rather than functioning as neutral tools, these systems selectively translate, flatten, and recompose local imaginaries, design vocabularies, and rhetorical forms. Such distortions are approached here not simply as technical limitations, but as epistemic symptoms of the asymmetries embedded in contemporary generative infrastructures. A central component of the exhibition was an AI-generated audiovisual layer. Four satirical short films, styled as “Pixar-like” animations, presented a tardigrade interviewing four “successful” Czech women, while three additional videos featured fictional male influencers performing polarised monologues on migration, left politics, and the pre-election climate. Produced entirely through AI-based image, animation, voice, sound, and script generation, these works mobilised speculative fiction as a mode of cultural diagnosis. The chapter argues that generative systems participate in the reconfiguration of political and cultural representation, reshaping not only aesthetic production but also the conditions under which locality becomes legible.
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Albín Kuchta: Virtual Spaces: Tools of Poetic Resistance or Censorship Devices?
Disegno 2025/1, page range: 148-65.
https://doi.org/10.21096/disegno_2025_1aku
This article analyses digital and virtual art spaces as ambivalent formations that may operate either as instruments of poietic resistance or as dispositifs of censorship. Engaging with Jacques Derrida’s theory of the archive, Bernard Stiegler’s critique of technocapitalism, and philosophical accounts of poiesis, the paper examines how institutional and non‑institutional virtual archives shape collective memory, affectivity, and regimes of visibility. Focusing on the Slovak context within Central and Eastern Europe, it demonstrates how Roma and queer communities are systematically marginalised within institutional archives and digitised museum platforms, where exclusion frequently assumes the form of soft or indirect censorship. At the same time, the study foregrounds the emancipatory potential of non‑institutional virtual spaces, social media, and AI‑mediated practices, which are increasingly appropriated by marginalised artists as tools of resistance. Through selected case studies of Roma and queer artistic practices, the article shows how digital and AI‑supported poiesis can generate counter‑archives, alternative affective frameworks, and new modes of political agency that contest hegemonic, racialised, and heteronormative norms. The paper concludes that virtual art spaces are not intrinsically emancipatory or oppressive; rather, their political significance depends on the conditions of access, control, and interpretation that govern archiving practices. It therefore calls for participatory and ethically grounded approaches to digital archiving and AI data governance in order to prevent the continued reproduction of institutional racism and cultural erasure.
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About the Authors
Disegno, 2025/1, page range: 168–70.