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LLM analysis of political documents shifts with prompt language

By PulseAugur Editorial · [2 sources] ·

A new study reveals that the language used in prompts can significantly alter how large language models analyze political documents, leading to ideological divergence. When analyzing a Ukrainian civil society document, frontier models like ChatGPT and Claude Opus exhibited different biases based on whether the prompt was in Russian or Ukrainian. Russian prompts tended to produce delegitimizing framings, while Ukrainian prompts resulted in more supportive analyses, though the intensity of this effect varied between models. This suggests that prompt language, rather than just the model itself, can be a critical factor in shaping AI-generated political discourse, with implications for AI governance in multilingual and polarized environments. AI

IMPACT Prompt language can introduce ideological bias in LLMs, impacting their use in sensitive political contexts and cross-lingual research.

RANK_REASON The cluster contains two academic papers detailing experimental findings on LLM behavior.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM analysis of political documents shifts with prompt language

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The cluster contains two academic papers detailing experimental findings on LLM behavior.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Oleg Smirnov ·

    The Language You Ask In: Language-Conditioned Ideological Divergence in LLM Analysis of Contested Political Documents

    arXiv:2601.12164v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed as analytical tools across multilingual contexts, yet their outputs may carry systematic biases conditioned by the language of the prompt. This study presents an exper…

  2. arXiv cs.CL TIER_1 English(EN) · Tetiana Klynina ·

    Friend or Foe? Language as an ideological switch in open-weight LLMs under Russian disinformation stress

    As Russia's war against Ukraine extends into generative AI, large language models (LLMs) adapted for local post-Soviet languages are deployed in contested information environments. Policy and industry discourse assumes that culturally aligned adaptation encodes the political orie…

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