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A World Bank report and documentary uncover that AI systems depend on a hidden workforce of 150-430 million low-paid data workers, often refugees or crisis-stricken populations in the Global South, who perform exploitative labeling and annotation tasks under secrecy.
This paper presents Eskwai for Students, a generative AI assistant for legal education in Ghana, using retrieval-augmented generation on a database of over 12K case laws and 1.4K legislation. Deployed in a 30-month study with 3.1K law students, it provides insights into AI usage in legal education in the Global South.
This paper introduces NSMQ Riddles, a novel benchmark using scientific and mathematical riddles from Ghana's National Science and Maths Quiz to evaluate Large Language Models, addressing the underrepresentation of Global South datasets in AI research.