Word embeddings reveal growing moral concern for people, animals and the environment.

The Enlightenment idea of historical moral progress asserts that civil societies become more moral over time. This is often understood as an expanding moral circle and is argued to be tightly linked with language use, with some suggesting that shifts in how we express concern for others can be considered an important indicator of moral progress. Our research explores these notions by examining historical trends in natural language use during the 19th and 20th centuries. We found that the associations between words denoting moral concern and words referring to people, animals, and the environment grew stronger over time. The findings support widely-held views about the nature of moral progress by showing that language has changed in a way that reflects greater concern for others.

Speciesism in everyday language.

Speciesism, like other forms of prejudice, is thought to be underpinned by biased patterns of language use. Thus far, however, psychological science has primarily focused on how speciesism is reflected in individuals' thoughts as opposed to wider collective systems of meaning such as language. We present a large-scale quantitative test of speciesism by applying machine-learning methods (word embeddings) to billions of English words derived from conversation, film, books, and the Internet. We found evidence of anthropocentric speciesism: words denoting concern (vs. indifference) and value (vs. valueless) were more closely associated with words denoting humans compared to many other animals. We also found evidence of companion animal speciesism: the same words were more closely associated with words denoting companion animals compared to most other animals. The work describes speciesism as a pervasive collective phenomenon that is evident in a naturally occurring expression of human psychology - everyday language.