AI Stories

AI STORIES: Narrative Archetypes for Artificial Intelligence, examines how large language models (LLMs) like GPT-4, trained on vast text and image data, may not only replicate historical biases but also narrative structures from their training materials, potentially impacting cultural diversity. The project leverages narratology to analyse training data and AI-generated content, focusing on whether these narratives render AI culturally specific.

The project is led by Jill Walker Rettberg, with Mahaut de Vareilles as research adviser and impact manager. The team includes postdoctoral fellows Anne Sigrid Refsumm, Zahra Rizvi, and Jessica Witte, doctoral candidate Mick with Berland, research assistant Elise Marie Strand Hagen, and data management expert Tone Merete Bruvik. We also regularly host guest researchers - overview of recent visitors and their contributions (external link).

If you are interested in this project and our research, you are welcome to contact us; we are always open to exploring potential collaborations.

We will be announcing a 3-year PhD position in Data Visualization, in collaboration with the UiB Data Viz group (external link), at the end of June 2026, with expected start date in late 2026/Jan 2027 (link will be shared here, and findable on JobbNorge and EURAXESS).

You may also wish to join us for our Critical AI Theory Discussion Lunches. We meet once or twice a month on Tuesdays at the CDN, and are open to anyone who has read the text for discussion, with hybrid participation possible. To receive announcements, please sign up for the mailing list (external link). The program for Autumn 2027 will be announced here [upcoming]. Check Jill's blog (external link) for past discussion topics.

About the project

The researchers will look at two central questions:

• How do narrative archetypes in training data shape the functioning and output of large language models?
• To what extent do the narrative archetypes of different cultures make machine learning models culturally specific?

The hypothesis emerged after an AI developed by Microsoft professed love during a conversation, illustrating AI's reliance on human narratives. AI STORIES argues that AI development now requires humanities' insight to understand its language and cultural dimensions. This research could influence AI policy, development, and digital literacy, emphasizing the need for cross-disciplinary collaboration.

AI STORIES conducts case studies on Scandinavian, Australian, and Indian narratives, contrasting them with the dominant North American narratives in LLMs. The project's methodology unfolds in three stages: establishing theoretical groundwork, testing theories experimentally, and synthesizing results to form a narratology of AI.

The project builds on the notion that storytelling is central to human culture, with narratives shaping our understanding of the world. It challenges the view of AI as "stochastic parrots" that mimic language patterns without understanding, proposing that narrative structures might be more significant than vocabulary or grammar in AI-generated content. Despite their novelty, LLMs are being explored for literary creation and analysis, with the humanities and social sciences contributing critical perspectives on AI's role in society.

AI STORIES posits that LLM outputs are influenced by deeper narrative structures than previously recognized, suggesting that addressing AI bias requires examining these underlying narratives rather than just sign proximity. The project aims to redefine the scientific understanding of AI bias and narrative influence, with significant implications for the study of narratives and AI research.

Selected publications

• Rettberg, Jill Walker. 2026, "AI-generated podcasts: Synthetic intimacy and cultural mistranslation in audio overviews from Google’s NotebookLM", https://doi.org/10.1177/01634437261452160 (external link)
• Rettberg, Jill Walker; Wigers, Hermann. 2026, "AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini", https://doi.org/10.12688/openreseurope.20576.1 (external link). For the underlying dataset: https://doi.org/10.18710/VM2K4O (external link)
• Refsum, Anne Sigrid. 2025, "“The Sweetheart in the Forest” and the Synthetic Storytellers", https://doi.org/10.3390/h14120230 (external link)
• Rettberg, Jill Walker. “Repeating Ourselves with Generative AI.” CounterText, vol. 10, no. 3, Dec. 2024, pp. 232–37. DOI.org (Crossref), https://doi.org/10.3366/count.2024.0360 (external link).
• Rettberg, Jill Walker. “How Generative AI Endangers Cultural Narratives.” Issues in Science and Technology, vol. 40, no. 2, Jan. 2024, pp. 77–79. DOI.org (Crossref), https://doi.org/10.58875/RQJD7538 (external link).

Download the five page project proposal

The "B1" or five page summary of the project proposal is available as a PDF (external link). This document describes the overall project plan.