Uganda’s Homegrown AI

When it comes to machine learning and artificial intelligence, one size does not fit all.

| October 2019

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Photo by Getty Images/mtcurado.

No single label (except multitalented, perhaps) can fully describe Daniel Mutembesa. He’s a poet, musician, DJ, semi-professional dancer, national Karate champion, and, of course, an engineer—all despite being only twenty-seven years old. When I met him front of the AI lab at Makerere we became fast friends and immediately fell into a spirited conversation about the cultures, traditions, and politics of Uganda. I was fascinated to meet someone in the lab who saw his work in computing as perfectly aligned with his interests in supporting his countrymen.

Mutembesa took me off campus to different and interesting parts of the city in his tiny Korean car. He taught me the indigenous names for Uganda’s national parks. By using these names he hoped to revive interest in the histories and traditions of his country. Part of the incredible diversity of Uganda comes from its more than forty indigenous languages. They are spoken in local communities without a national language to lean on for universal communication, except for the English used primarily in metropolitan areas.

Like nearly everyone in Uganda, Mutembesa comes from its tribal regions: the Ankole and Tooro parts of the southwest of the country (the latter borders the Democratic Republic of Congo). Learning about his nation opened my eyes to a sad trend of historic and cultural erasure. Mainstream entertainment produced for and accessed by Ugandan audiences often adheres to the Western brand, as when DJs fake American accents on the radio and African TV programs mimic American Idol and Survivor. Western webpages dominate the internet. Mutembesa sees this as an invasion of national and cultural consciousness by Western norms and products.9 I asked him how the AI lab sees itself relative to these cultural and global forces. Is computing simply seen as a vehicle of “being modern” (aka imitating the West) or can it revive and support the identities and values of the culture’s richly diverse traditions and communities?



Mutembesa passionately believes in the latter. He is designing AI systems that learn from Ugandan farmers’ decisions about harvesting crops. He has built a machine-learning model that considers the way farmers make choices about using treatments that agricultural scientists suggest. Potential problems arise, he tells me, when applying a model developed from afar to the Ugandan context. But an alternate approach may come from understanding that the strength of game theory lies in the relatively few assumptions upon which it is built.

Game theory considers decisions made to either cooperate or compete with participants in social settings, and the factors that shape these choices. The lab’s model allows the Makerere team to learn the unexpected. For example, they found that the National Agricultural Institute, a partner of the AI lab in Mutembesa’s project, has great sway with farmers—far more, in fact, then the lab would have in paying them to participate. Praise matters more than money; knowing this important cultural value, the team collaborated with farmers and applied technology to maximize yields and harvests.

Though it gained independence from the British in 1962, Uganda continues to face uneven relationships relative to the world’s political superpowers. There is a tendency to blindly embrace the media, technologies, and ideas of Europe and the United States. As a result, Mutembesa says, “We, in Uganda, have a strong tendency to take on blanket recommendations. From our technology, to our research, to our systems of education and health, even the names we give to our lands and parks, we are forced to follow the funding and the rules of the funder.”

What does this mean for the AI lab? The challenges it faces are local, the questions they wish to answer are local, the communities, plants and animals with which they work are local. But the funding models are not. As a result, the lab may not always be answering the “right” questions when it comes to serving their country.

Why don’t these researchers move into the startup world and begin a chain reaction that could, eventually, create more wealth within the nation? The hurdles are too high. The national government gives almost no support to entrepreneurs. Unlike in nearby Nairobi, Kenya’s capital, there is little history of foreign investment in technology in the Ugandan capital and country as a whole. Researchers working in Kampala have more secure incomes than those working in business. The risks are too high for entrepreneurs to take on labor costs and invest heavily in their city and country.

Nonetheless, Mutembesa remains hopeful. Despite the complacency with which Ugandans view their lives and the uncritical ways they tend to applaud the West, he believes in the deep, living heritage and identity within his country. That identity is evident in the land and in the languages, dances, and music from the nation’s numerous indigenous communities. These forms of cultural expression are the “knowledge of the people,” he says, and are the “basis for which technology and innovation should be developed to serve our communities.”

This example resonates with the perspective of Dambisa Moyo, an internationally recognized author from Zambia, and an economist specializing in African developmental economics. In her book Dead Aid she pulls no punches when she criticizes African dependency on foreign aid. Because of it, she says, “Misery and poverty have not ended but increased. [Aid] has been, and continues to be, an unmitigated political, economic, and humanitarian disaster for most parts of the developing world.”

Moyo points out that Uganda, like many of its neighbors, is a youthful nation with 50 percent of the population younger than fifteen. She argues that aid disempowers this young population by placing her fellow Africans in a subservient position, elevating foreign goals over local creativity. Subsidies for farmers guaranteed by the World Trade Organization, for example, might seem helpful but in reality they can harm local economies. Subsidies drive down the prices of staple goods and leave farmers in financial instability, unable to negotiate the terms by which they buy and sell.  We can see evidence of this with global trade market, where Africa represents only 2 percent of overall activity.

My time in East Africa, and specifically Uganda, does not necessarily echo Moyo’s position. Certain types of aid, including a Google Research Initiative, have supported the development of the laboratory of scholars and their students at Makerere, one of the continent’s top universities. Emerging from this has been impressive coordination among scholars, researchers, and engineers across all of Africa.

But has such aid forced a ceiling on growth? Makerere’s AI lab reveals that external aid, lacking concern for the culture and voices of Ugandan citizens, is no panacea. Uganda’s neighbor to the West, Rwanda, once faced a similar situation in relation to aid from the United States and the International Monetary Fund (IMF). Instead of simply taking the aid, Rwanda gave the IMF an ultimatum: let us accept your aid but on our terms, where it will enter the right hands and take the right paths to grow the economy. The push and pull of independence versus dependence is a common story when we look at technology across the world.




Excerpted from Beyond the Valley: How Innovators around the World Are Overcoming Inequality and Creating the Technologies of Tomorrow by Ramesh Srinivasan. Reprinted with permission from The MIT PRESS. Copyright 2019.

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