Machine Learning in Africa

by Lily Adelstein

October 7, 2021 3 min read

Above: Andrew Blumenfeld, co-founder of Telepath, and Lily Adelstein, creative project manager, discuss Google, ML and Africa.

Yesterday, Google announced a $1 billion investment to increase broadband access and fund startups across Africa over the next 5 years. Part of this investment includes Equiano, a subsea cable that will connect Europe and Africa. Google claims this will reduce broadband costs, increase internet speeds and “provide 20 times more network capacity than the last cable built to serve Africa.” With this kind of investment in technology infrastructure in Africa along with the growing number of startups, we will see a growing use of machine learning in the region to help startups create a competitive advantage, drive new business opportunities and foster innovation.

During Google’s event yesterday, two startups that were highlighted use artificial intelligence (AI) and machine learning (ML) already for their businesses. One was Tambua Health, which is a company based in Nairobi, Kenya, that uses ML to detect respiratory illnesses. The other is AirQo, a company based out of Kampala, Uganda, that uses AI and sensors to monitor air quality. As more businesses in Africa come online, machine learning can help accelerate the work of these teams. 

Google reports that over the next 5 years, we will see more than 300 million people in Africa come online for the first time. This, in part, means more of a market for software companies both in the region and abroad. Access to the internet also means access to a world of educational content, like Free Code Academy, Coursera, Linkedin Learning, EdX or even Google’s own courses. This access will likely educate new generations of entrepreneurs on topics like software development.

Google is investing in a long game here. Providing infrastructure and skills to create and develop a stronger consumer market in Africa. Google can make product, after product, after product, for users across Africa, but it is a software company and without access to high speed internet and devices, it is hard for Google products to currently make a dent in the region.

While we must be wary of Google’s mammoth size global footprint, in bringing this level of access to Africa, it could be laying the foundation for a new Google or some other successful business to thrive. Machine learning can be beneficial to startups in Africa in the following ways:

  1. Bringing continuous improvements to products. Machine learning algorithms can learn from new data to improve a model used for recommendations or predictions. More data can increase the models accuracy in these tasks. This can result in a more personalized experience for a user. 
  2. Automating decision-making tasks. For example, machine learning can be used to classify documents, saving someone lots of time. 
  3. Identifying trends and patterns. This could be useful in identifying customer segmentations and demand seasonality.
  4. Industry agnostic. Machine learning is being used in almost every industry, from healthcare to finance to energy, so no matter the type of company you start, machine learning could have applications. 

Google’s investment in Africa shines a spotlight on the growing market of startups and entrepreneurs building software solutions in the region. Google’s investment in infrastructure will mean that more entrepreneurs and startups will come online and create software solutions. It is likely this will lead to a greater demand in the region for machine learning, which is used to help businesses create a competitive advantage, drive new business opportunities and foster innovation.

Sources:

https://www.builtinafrica.io/videos/tambua-health-machine-learning

https://techcrunch.com/2021/02/11/how-african-startups-raised-investments-in-2020/

https://www.brookings.edu/research/spotlighting-opportunities-for-business-in-africa-and-strategies-to-succeed-in-the-worlds-next-big-growth-market/

https://twitter.com/googleafrica/status/1445676452528205824

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