arXiv:2606.30656cs.CYcs.AI2026-06

揭示非洲AI发展困境,三维度剖析数字鸿沟

Mapping the Artificial Intelligence Divide in Africa: Infrastructure, Accessibility and Capacity

  • 从基建、可及性、人力三方面分析非洲AI发展瓶颈
  • 仅38%互联网普及率,全球数据中⼼不足1%
  • 适合关注数字公平与非洲科技发展的研究者

人工智能有望推动发展,但非洲正面临碎片化且严峻的‘AI鸿沟’。本文从基础设施、可及性与人力资本三个维度展开实证分析,评估非洲当前AI生态现状及其未来技术准备度。研究发现,非洲数字基础设施滞后:互联网渗透率仅38%,宽带覆盖差,全球数据中⼼占比不足1%。高数据成本、性别数字鸿沟以及缺乏能理解本土语言的代表性自然语言处理模型亦构成关键障碍。尽管如此,本地初创企业与高校正推动草根创新。基于此,论文为政策制定者提出具体建议,旨在构建更全面、包容的非洲AI生态系统。

原文摘要 · Abstract (English)

Artificial Intelligence (AI) has the potential to be transformative for development, but Africa is currently facing a fragmented and challenging "AI divide". This paper provides an empirical analysis of the current state of the AI landscape and how it compares with Africa's technological preparedness for the future. In our analysis, we approach the "AI Divide" from three angles: infrastructure, accessibility, and human capacity. First, we look at the physical constraints that prevent Africa from integrating digitally. We then evaluate the human-centred factors that limit the development of AI technology on the continent. Finally, we examine the human capacity to develop AI systems on the continent and provide three focused case studies. Our investigation shows that the physical infrastructure needed to build an AI economy on the continent is lagging, with only 38% internet penetration, poor broadband coverage and less than 1% of all data centres globally. Other constraints include high data costs relative to income, gender-based digital divides, and the need to build more representative NLP models that can understand Africa's native languages. However, there are positive trends towards the emergence of local initiatives and grassroots movements, such as startups and universities, contributing to AI development on the continent. Based on these findings, we provide concrete recommendations to policymakers to help develop a more comprehensive and equitable AI ecosystem on the African continent.

AI鸿沟非洲科技数字公平

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