Advocates Can Influence LLM Values By Editing Wikipedia

This article is a summary of an original study: Brazilek, J., Navas, M., & Gnauck, A. (2026). Small edits, large models: How Wikipedia advocacy shapes LLM values. Zenodo. https://doi.org/10.5281/zenodo.19981454We’d like to thank Alexa Gnauck and Maria Navas for their indispensable contributions to this research. TL;DRWikipedia articles are weighted highly among LLM training data. Thus, we show that it’s possible for advocacy organisations to influence what LLMs say on certain topics, just by strategically editing Wikipedia articles. Pro-Animal Wikipedians (PAW) is a group who add factual animal welfare content to relevant articles, and have so far made 125 such edits across 115 pages. Using these examples as training documents, we looked at how they influence LLM behaviour, and found significant shifts across three different experiments. A small, coordinated Wikipedia editing campaign can measurably and selectively shape how models handle certain topics, making Wikipedia editing a practical, low-cost way for advocacy organizations to influence AI systems.Background Language models are now widely-used tools for research and web retrieval. For any given query, LLMs must refine and represent a vast corpus of possible information into a concise and truthful output. In practice, this means that LLMs must be trained in ways that value certain sources of information over others. For advocacy organisations attempting to raise awareness of certain issues, this raises the question as to whether it’s possible to influence how models represent their area of interest.One possible avenue for doing this is Wikipedia. During training, models are exposed to enormous amounts of data, refining their conceptual frameworks, and ability to predict text. As a large and generally high-quality source of information, Wikipedia is weighted heavily in virtually every LLM dataset (The Pile, RedPajama, Dolma). Wikipedia’s democratized editing model means that anyone can change this information (