The current methods for determining the "best" AI models, primarily through benchmarks and leaderboards, overlook significant global disparities in AI access and capability. Data indicates a growing gap in AI tool usage between the Global North and Global South, with countries like the UAE and Singapore showing high adoption rates. Furthermore, developing regions, particularly Africa and Latin America, possess minimal global data center capacity, prompting calls for international funds to build AI infrastructure. A key overlooked disparity is language, as different languages require varying numbers of tokens for AI processing, potentially leading to higher costs and slower service for non-English speakers. AI
IMPACT Highlights potential for AI to exacerbate global inequalities if access and cost are not addressed.
RANK_REASON The item is an opinion piece discussing the implications of AI development and access, rather than a direct release or event.
- Africa
- AI diffusion
- Global North
- Global South
- Latin America
- OpenAI
- Singapore
- Stanford University
- United Arab Emirates
- United Nations
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