A global AI community requires language-diverse publishing
This addresses the issue of language diversity for global AI scientists and readers, but it is incremental as it proposes changes rather than implementing new methods.
The paper tackles the problem of English dominance in AI research publishing, arguing it reinforces linguistic exclusion and extraction, and proposes alternative futures such as multilingual conferences and peer review policies.
In this provocation, we discuss the English dominance of the AI research community, arguing that the requirement for English language publishing upholds and reinforces broader regimes of extraction in AI. While large language models and machine translation have been celebrated as a way to break down barriers, we regard their use as a symptom of linguistic exclusion of scientists and potential readers. We propose alternative futures for a healthier publishing culture, organized around three themes: administering conferences in the languages of the country in which they are held, instructing peer reviewers not to adjudicate the language appropriateness of papers, and offering opportunities to publish and present in multiple languages. We welcome new translations of this piece. Please contact the authors if you would like to contribute one.