Tech Policy Press is a nonprofit media and community venture intended to provoke new ideas, debate and discussion at the intersection of technology and democracy. We publish opinion and analysis.
Tech Policy Press - Technology and Democracy
Tech Policy Press is a nonprofit media and community venture intended to provoke new ideas, debate and discussion at the intersection of technology and democracy. We publish opinion and analysis.
State media control influences large language models
Millions of people around the world query large language models (LLMs) for information. Although several studies have compellingly documented the persuasive potential of these models1–10, there is limited evidence of who or what influences the models themselves, leading to a flurry of concerns about which companies and governments build and regulate the models. Here we show through six studies that government control of the media across the world already influences the output of LLMs via their training data. We use a cross-national audit to show that LLMs exhibit a stronger pro-government valence in the languages of countries with lower media freedom than in those with higher media freedom. This result is correlational, so to triangulate the specific mechanism of how state media control can influence LLMs, we develop a multi-part case study on China’s media. We demonstrate that media scripted and curated by the Chinese state appears in LLM training datasets. To evaluate the plausible effect of this inclusion, we use an open-weight model to show that additional pretraining on Chinese state-coordinated media generates more positive answers to prompts about Chinese political institutions and leaders. We link this phenomenon to commercial models through two audit studies demonstrating that prompting models in Chinese generates more positive responses about China’s institutions and leaders than do the same queries in English. The combination of influence and persuasive potential across languages suggests the troubling conclusion that states and powerful institutions have increased strategic incentives to leverage media control in the hopes of shaping LLM output.
State media control influences large language models
Millions of people around the world query large language models (LLMs) for information. Although several studies have compellingly documented the persuasive potential of these models1–10, there is limited evidence of who or what influences the models themselves, leading to a flurry of concerns about which companies and governments build and regulate the models. Here we show through six studies that government control of the media across the world already influences the output of LLMs via their training data. We use a cross-national audit to show that LLMs exhibit a stronger pro-government valence in the languages of countries with lower media freedom than in those with higher media freedom. This result is correlational, so to triangulate the specific mechanism of how state media control can influence LLMs, we develop a multi-part case study on China’s media. We demonstrate that media scripted and curated by the Chinese state appears in LLM training datasets. To evaluate the plausible effect of this inclusion, we use an open-weight model to show that additional pretraining on Chinese state-coordinated media generates more positive answers to prompts about Chinese political institutions and leaders. We link this phenomenon to commercial models through two audit studies demonstrating that prompting models in Chinese generates more positive responses about China’s institutions and leaders than do the same queries in English. The combination of influence and persuasive potential across languages suggests the troubling conclusion that states and powerful institutions have increased strategic incentives to leverage media control in the hopes of shaping LLM output.
PropagandaScope
Tracking articles from newspapers. Real-time analysis of propaganda transmission patterns.
How propaganda exploits the infrastructure of truth: A case study of #IStandWithPutin
This paper investigates the #IStandWithPutin hashtag campaign as a case study to conceptualise “infrastructural propaganda,” an influence strategy that manipulates the invisible processes and syste...
Replication Data for "State Media Control Influences Large Language Models"
Replication dataset for "State Media Control Influences Large Language Models," forthcoming in Nature (https://doi.org/10.1038/s41586-026-10506-7). We show through six studies that government control of the media across the world influences the output of large language models (LLMs) via their training data.
Replication Data for "State Media Control Influences Large Language Models"
Replication dataset for "State Media Control Influences Large Language Models," forthcoming in Nature (https://doi.org/10.1038/s41586-026-10506-7). We show through six studies that government control of the media across the world influences the output of large language models (LLMs) via their training data.
AI Policy • States Newsroom
AI Policy States Newsroom is, above all, dedicated to journalism practiced by people. We believe in the power of having on-the-ground reporters covering our communities with the finesse and nuance that only human interaction can produce. We also recognize the power and potential of generative AI. We are open to the responsible and transparent use […]
Why Don’t We Learn from Social Media? Studying Effects of and Mechanisms behind Social Media News Use on General Surveillance Political Knowledge
Does exposure to news affect what people know about politics? This old question attracted new scholarly interest as the political information environment is changing rapidly. In particular, since c...
Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena
<p>Download the pdf here. Executive Summary Despite growing interest, the effects of AI on the news industry and our information environment — the public arena — remain poorly understood. Insufficient attention has also been paid to the implications of the news industry’s dependence on technology companies for AI. Drawing on 134 interviews with news workers […]</p>
State Media Control Influences Large Language Models – State Media & LLMs
Hannah Waight1,2, Eddie Yang1,3, Yin Yuan4, Solomon Messing5, Margaret E. Roberts4, Brandon M. Stewart6, Joshua A. Tucker5,7
Could this be the beginning of the end for the billionaire-owned media propaganda blitz?
A campaign to free our national press from foreign billionaires like Rupert Murdoch is gaining momentum and attracting big-name support
State Media Monitor Global Dataset 2025
This dataset provides comprehensive information on the governance, funding, and editorial independence of state and public media outlets worldwide. In 2025, the State Media Monitor covers 170 countries, tracking changes in media governance models, funding mechanisms, and degrees of political control. The dataset underpins the annual State Media Monitor Global Study and supports comparative research in journalism, media policy, and governance. Access the full dataset here: https://www.statemediamonitor.com
A Well-funded Moscow-based Global ‘News’ Network has Infected Western Artificial Intelligence Tools Worldwide with Russian Propaganda
A full version of this report is available through NewsGuard’s Reality Check.
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EKI and Propastop Studied AI Resistance to Propaganda
Fresh comparisons of large language models show that AI’s ability to recognise Kremlin propaganda varies dramatically. At first glance, the leading models appear reliable, but targeted testing reveals that some of them remain surprisingly vulnerable to manipulation.
