The societal impact of artificial intelligence (AI) is global, yet the narrative around AI often centers around perspectives from the U.S. and Europe. Unsurprisingly—in a tech ecosystem that spans the planet—AI is powering change everywhere. International researchers are making AI breakthroughs in sectors as varied as healthcare, fintech, education, and environmental science, and the potential of Large Language Models (LLMs) is being investigated from India to Tanzania. However, country-level dynamics—including socioeconomics and linguistic diversity—can shape a nation’s AI priorities, flashpoints, and aspirations.
Seeking a ‘snapshot’ of the global outlook for AI, experts were asked to share their thoughts about developments and challenges in their countries.
Chika Yinka-Banjo, a professor of computer science at Nigeria’s University of Lagos, reports that Natural Language Processing (NLP) and LLMs are currently the “most common” AI research fields in Nigeria. “These technologies can be applied to various sectors, including customer service, content creation, and language translation, which could be beneficial in the diverse linguistic landscape of West Africa,” she says.
Neema Mduma, a computer science and machine learning expert at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Tanzania, explained that that country’s government is prioritizing tech investment and actively integrating AI into its platforms. The judiciary, for example, is incorporating AI into its new transcription and translation system, which “will undergo training using Swahili dialects from diverse communities, spanning from Tanzania mainland to Zanzibar, as well as Tanzanian English attributions,” Mduma says.
AI solutions also are being implemented in education and agriculture—Mduma’s own research currently centers on developing AI tools to help smallholder farmers better control pests and diseases.
On a connected planet, there are clear universal trends in the AI outlook, yet some national distinctions—driven by factors like geography, cultural diversity, and socioeconomics—do appear. However, the starkest divergences may only emerge as countries choose whether to take a collaborative or competitive approach to AI regulation and guardrails, a complexity that is just starting to unfold.
Source: CACM
