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Study finds GPT-5, Claude Sonnet, Gemini rate China- and Russia-endorsed policies lower than identical US- or EU-endorsed ones

A new arXiv preprint reports an endorsement experiment in which four LLMs (GPT-5, Claude Sonnet, Gemini, and a fourth unnamed model) evaluated identical international economic and security policies randomly attributed to the US, EU, China, or Russia. In the numeric-only condition, models rated China- and Russia-endorsed policies substantially lower than the same policies endorsed by the US or EU, revealing implicit geopolitical bias.

0 engagement·1 source·Fri, Jul 10, 2026, 10:26 AM
The study, posted on arXiv on July 10, 2026, tests whether LLMs' policy evaluations are shaped by geopolitical cues. Four models—GPT-5, Claude Sonnet, Gemini, and one other—were given policy descriptions randomly attributed to the United States, the European Union, China, or Russia. In a numeric-only scoring condition, policies endorsed by China and Russia received significantly lower scores than identical policies endorsed by the US or EU. The finding raises concerns about the use of LLMs for unbiased policy analysis and decision support.

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Gemini(model)arXiv(tool)Claude Sonnet(model)GPT-5(model)Geopolitical bias(concept)

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