Analysis / Coming to Life: Artificial Intelligence in Africa

 

coming to life:

Artificial intelligence in Africa

 
 

This report was written by Magpie Advisory Founder and CEO, Aleksandra Gadzala, in her role as Senior Nonresident Fellow with The Atlantic Council. It can also be found in our Africa and Disruptive Technology newsfeeds.


Introduction

Artificial intelligence (AI), which enables machines to exhibit human-like cognition, is unleashing the next wave of digital disruption. Global investment in AI skyrocketed to somewhere between $20 billion and $30 billion in 2016, with 90 percent of this spent on research and development and deployment, and 10 percent on AI acquisitions. Investment has so far been dominated by digital giants like Google and Baidu, but private investors are also jumping in, fronting an estimated $4-$5 billion in venture capital in 2016, and another $1-$3 billion in private equity. While many uses of AI are still in the experimental phase, commercial applications are already surfacing in a variety of sectors: AI systems filter emails, recommend items for purchase, provide legal advice, and drive cars. 

The success of mobile technologies (tech) across Africa is prompting speculation among tech investors about whether AI applications will also take root in African nations. Mobile technologies, after all, have permitted African nations to dramatically increase their communication capabilities while leapfrogging the need for old-fashioned infrastructure. Will AI offer similar benefits?

Unfortunately, except in a handful of countries—namely Kenya, South Africa, Nigeria, Ghana, and Ethiopia—the application of AI is a chimera, not a reality. The critical factors necessary for the technology to take hold are woefully absent across most of the continent, and many African countries remain incapable of requisite reforms in the areas of data collection and data privacy, infrastructure, education, and governance. Without those reforms, there is little chance that most African nations will be able to exploit AI technologies to advance sustainable development and inclusive growth. The specter of automation threatens to leave these countries behind. 

But there are a few African countries where the factors needed for the successful adoption of AI technologies are rapidly converging. In these nations, AI initiatives are still mostly small-scale, pilot, or ad hoc—but appear promising and have thus attracted significant backing from global corporations. This issue brief examines the obstacles to AI’s broader adoption across the African region and explores the enabling factors underpinning its promise in the handful of African countries where, despite significant challenges, AI ventures are enjoying early success. 

An Uneasy Environment for AI 

At its most basic, artificial intelligence uses algorithmic techniques loosely modeled on the human brain to enable machines to discover patterns, generate insights from the data to which they are exposed, and then apply those lessons learned to future decision making and predictions. AI, in the form of virtual assistants like Apple’s Siri or Amazon’s Alexa, uses algorithms to match single voiceprints against subsequent repetitions of the same phrase to learn and predict natural-language requests. Learning thermostats like Nest, which was acquired by Google in 2014 for $3.2 billion, also use behavioral algorithms to learn individual heating and cooling needs and adjust the temperature in the user’s home based on her personal preferences. AI is also now being used in more complex applications including the analysis of large genome sets in an effort to prevent diseases, and the mapping of human mobility patterns to predict and control humanitarian crises. 

To perform such functions AI depends on robust digital foundations, which include the availability of large volumes of data—usually referred to as “big data.” Machines can analyze this data to learn, make connections, and arrive at decisions. But AI also relies on significant know-how among its human adopters: industry leaders must know how to successfully implement AI into their operations, and consumers must be comfortable with its use (and that includes a reasonable assurance of data privacy). With the exceptions of Kenya, South Africa, Nigeria, Ghana, and Ethiopia— where these factors are rapidly coming together on the back of other enabling factors—most African countries currently struggle to meet any or all of these requirements. 

Africa’s Data Challenge

The near-ubiquity of mobile phones—nearly one per person—and the growing popularity of social media and messaging applications (apps) across Africa has made data more readily available. Governments, development programs like the World Bank’s “Listening to Africa” initiative, and market research companies increasingly rely on mobile phone surveys and user data to collect insights into local populations. Still, even in countries where AI holds promise, the quality, timeliness, and availability of data on critical indicators— data on births and deaths; growth and poverty; taxes and trade; health, schooling, and safety; and land and the environment—and the surrounding necessary data protections are often poor in quality or missing.

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