SOURCE-LINKED INTELLIGENCE
Narrative Archetypes for Artificial Intelligence
Narrative Archetypes for Artificial Intelligence AI STORIES is premised on the hypothesis that narrative archetypes fundamentally structure the output of contemporary artificial intelligence (AI). Large language models (LLMs) like GTP-4 are trained on vast quantities of text and images and generate new texts that are statistically similar to the training data. The scientific consensus acknowledges that LLMs replicate and sometimes exacerbate historical biases in their training data. AI STORIES proposes that LLMs are also affected by a deeper bias: that of the narrative structures in the social media posts, news stories, marketing blurbs and novels the models are trained on. If this is the case it will deeply impact how we use and apply AI, and how we think about bias and cultural diversity in AI models. Currently available LLMs are largely trained on English-language texts, with a heavy weighting towards the Un
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 2500000
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.