  In this position paper, we explore standard language ideology in language
generated by large language models (LLMs). First, we outline how standard
language ideology is reflected and reinforced in LLMs. We then present a
taxonomy of open problems regarding standard language ideology in AI-generated
language with implications for minoritized language communities. We introduce
the concept of standard AI-generated language ideology, the process by which
AI-generated language regards Standard American English (SAE) as a linguistic
default and reinforces a linguistic bias that SAE is the most "appropriate"
language. Finally, we discuss tensions that remain, including reflecting on
what desirable system behavior looks like, as well as advantages and drawbacks
of generative AI tools imitating--or often not--different English language
varieties. Throughout, we discuss standard language ideology as a manifestation
of existing global power structures in and through AI-generated language before
ending with questions to move towards alternative, more emancipatory digital
futures.
