Machine Intelligence in Africa: a survey

TL;DR

This survey reviews recent advances in machine intelligence in Africa, emphasizing culture-aware ethics, local language applications, and the potential for inclusive economic growth across 54 countries.

Contribution

It provides a comprehensive overview of MI developments in Africa, highlighting culture-aware approaches and ethical considerations often overlooked in global models.

Findings

Growth in African audio datasets enables localized MI applications.

Current MI tools lack cultural awareness and ethical considerations.

Diverse use cases across industries and sectors in Africa.

Abstract

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.