Mind the (Language) Gap: Mapping the Challenges of LLM Development in Low-Resource Language Contexts
This white paper maps the LLM development landscape for low-resource languages, highlighting challenges, trade-offs, and strategies to increase investment; prioritize cross-disciplinary, community-driven development; and ensure fair data ownership.
This white paper, produced in collaboration with Black in AI, presents considerations for the Congressional Black Caucus’s policy initiatives by highlighting where AI holds the potential to deepen racial inequalities and where it can benefit Black communities.
In this response to the U.S. Agency for International Development’s (USAID) request for information on the development of an AI in Global Development Playbook, scholars from Stanford HAI and The Asia Foundation call for an approach to AI in global development that is grounded in local perspectives and tailored to the specific circumstances of Global Majority countries.
