Due to the widespread use of large language models (LLMs) in ubiquitous
systems, we need to understand whether they embed a specific worldview and what
these views reflect. Recent studies report that, prompted with political
questionnaires, LLMs show left-liberal leanings. However, it is as yet unclear
whether these leanings are reliable (robust to prompt variations) and whether
the leaning is consistent across policies and political leaning. We propose a
series of tests which assess the reliability and consistency of LLMs' stances
on political statements based on a dataset of voting-advice questionnaires
collected from seven EU countries and annotated for policy domains. We study
LLMs ranging in size from 7B to 70B parameters and find that their reliability
increases with parameter count. Larger models show overall stronger alignment
with left-leaning parties but differ among policy programs: They evince a
(left-wing) positive stance towards environment protection, social welfare but
also (right-wing) law and order, with no consistent preferences in foreign
policy, migration, and economy.

通过一系列的测试，我们评估了大型语言模型（LLMs）对政治表态的可靠性和一致性，结果表明 LLMs 的态度可靠性随参数数量的增加而增加，较大的模型整体上更偏向左翼政党，但在各项政策方案中存在差异。它们对环境保护、社会福利、法律和秩序表现出（左翼）积极的态度，但对外交政策、移民和经济没有一致的偏好。