Geopolitical Divisions Across Languages in Large Language Models

2026-09-17

AI Summary

研究探讨了不同语言提问时AI对乌克兰战争评估的差异，通过让GPT、Claude和Gemini评估112种语言中的20个声明，揭示了地缘政治偏见的存在。

Abstract

People increasingly turn to AI chatbots for news and explanations of world events. But do they receive the same political answers when they ask in different languages? Here we show that the language of a question can change how the same AI systems assess the war in Ukraine. We ask GPT, Claude and Gemini to evaluate twenty statements about the war in 112 languages, collecting 67,200 responses. The balance between Russia-leaning and Ukraine-leaning responses differs across languages. When we group responses by countries' official languages, they follow a pattern resembling worldwide political divisions: relatively more Russia-leaning answers correspond to more favourable public views of Russia, less support for Ukraine in United Nations votes, and less aid to Ukraine. The broad pattern recurs across all three models and remains when individual statement pairs are removed. Our findings suggest a possible route through which information warfare may shape the text used to train AI models, which may in turn spread geopolitical biases.

Problem

• Geopolitical Divisions
• Large Language Models
• Ukraine War
• Political Bias

Innovation

• Geopolitical Biases
• Language Models
• Information Warfare
• Cross-lingual Analysis