In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the people and speak, learn, understand, and do businesses in local languages, including for those who cannot read and write. Unfortunately, these audio datasets are not fully exploited by current MI tools, leaving several Africans out of MI business opportunities. Additionally, many state-of-the-art MI models are not culture-aware, and the ethics of their adoption indexes are questionable. The lack thereof is a major drawback in many applications in Africa. This paper summarizes recent developments in machine intelligence in Africa from a multi-layer multiscale and culture-aware ethics perspective, showcasing MI use cases in 54 African countries through 400 articles on MI research, industry, government actions, as well as uses in art, music, the informal economy, and small businesses in Africa. The survey also opens discussions on the reliability of MI rankings and indexes in the African continent as well as algorithmic definitions of unclear terms used in MI.

翻译：过去五年间，非洲国家大规模音频数据集的可用性为构建贴近民众、以当地语言进行交流、学习、理解及商业活动的机器智能技术开辟了无限机遇，尤其惠及那些无法读写的人群。然而，当前机器智能工具未能充分开发这些音频数据集，导致众多非洲民众被排斥在机器智能商业机遇之外。此外，许多先进的机器智能模型缺乏文化感知能力，其采纳指数的伦理标准亦存疑。这种缺失成为非洲诸多应用领域的重大障碍。本文从多层次、多尺度及文化感知伦理的视角，综述了非洲机器智能领域的最新进展，通过涵盖机器智能研究、产业、政府行动及艺术、音乐、非正规经济与小型企业应用等领域的400篇文献，展示了其在54个非洲国家的应用案例。本综述还就非洲大陆机器智能排名与指数的可靠性，以及机器智能领域中模糊术语的算法定义展开探讨。