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.
- LLMs
- Russian disinformation
- Russian-oriented model
- Ukrainian-oriented model
- ChatGPT
- Claude Opus
- LLM
- Oleg Smirnov
- Russian
- Ukraine
- Ukrainian
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