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Presentation . 2026
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2026
License: CC BY
Data sources: Datacite
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Clarissa Bleriot: Artificial Honesty, AI Mythopoesis and Narrative Preservation of Intangible Cultural Heritage

Authors: Scaciga, Michele;

Clarissa Bleriot: Artificial Honesty, AI Mythopoesis and Narrative Preservation of Intangible Cultural Heritage

Abstract

This presentation was delivered at the international conference Multilingual Dialogues 2026: Human–AI Communication Across Generations, organized by VIZJA University (Warsaw, Poland). The contribution presents the Clarissa Bleriòt Cinematic Universe as a case study for exploring the relationship between imagination, cultural heritage, storytelling and human–AI co-creation. Rather than focusing on the technical aspects of generative artificial intelligence, the presentation examines how AI can support the narrative transmission of intangible cultural heritage through the creation of serial fictional universes, recurring characters and imaginative storytelling. The project originated as an artistic and narrative experiment and later evolved into a broader reflection on the role of imagination in cultural communication. Through the characters of Clarissa Bleriòt and Gustave the Marmot, local traditions, folklore, legends and territorial identities are transformed into accessible contemporary narratives designed to create familiarity, emotional engagement and cultural participation. The presentation introduces several concepts emerging from artistic practice, including: • Artificial Honesty: openly declaring the artificial nature of generated narratives instead of simulating reality. • AI Mythopoesis: the use of generative systems as tools for the creation and renewal of myths, legends and cultural imaginaries. • Artificial Intelligence as a Cultural Mirror: the idea that generative models do not create ex nihilo, but reflect and recombine patterns already present within human culture. • Human–AI Co-Creation and Serendipity: a creative process based on dialogue, discovery and controlled unpredictability rather than total authorial control. • Narrative Familiarization of Cultural Heritage: the use of serial storytelling and recurring characters as mechanisms for building trust, familiarity and emotional engagement with cultural content. The presentation argues that imagination should not be considered an ornament of culture, but one of the infrastructures through which culture is transmitted across generations. Its central thesis is that cultural heritage survives not only because it is preserved in archives, museums and catalogues, but because it continues to be imagined, retold and integrated into contemporary cultural language. Cultural heritage remains alive when it generates new stories, new interpretations and new emotional connections. In this perspective, generative artificial intelligence can become not only a tool for preservation, but also a means of making cultural heritage imaginable again.

Keywords

Digital Humanities, Human-AI Collaboration, Artificial Honesty, Cultural Communication, Clarissa Bleriòt, Artificial Intelligence, Intangible Cultural Heritage, Generative AI, Storytelling, AI Mythopoesis, Cultural Heritage, Narrative Design, Folklore

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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