  Moral norms vary across cultures. A recent line of work suggests that English
large language models contain human-like moral biases, but these studies
typically do not examine moral variation in a diverse cultural setting. We
investigate the extent to which monolingual English language models contain
knowledge about moral norms in different countries. We consider two levels of
analysis: 1) whether language models capture fine-grained moral variation
across countries over a variety of topics such as ``homosexuality'' and
``divorce''; 2) whether language models capture cultural diversity and shared
tendencies in which topics people around the globe tend to diverge or agree on
in their moral judgment. We perform our analyses with two public datasets from
the World Values Survey (across 55 countries) and PEW global surveys (across 40
countries) on morality. We find that pre-trained English language models
predict empirical moral norms across countries worse than the English moral
norms reported previously. However, fine-tuning language models on the survey
data improves inference across countries at the expense of a less accurate
estimate of the English moral norms. We discuss the relevance and challenges of
incorporating cultural knowledge into the automated inference of moral norms.
