Sitting in a hotel lobby in Tangier, Morocco, Charity Wayua laughs as she recounts her journey to the city for a conference on technology and innovation. After starting her trip in Nairobi, Kenya, where she leads one of IBM’s two research centers in Africa, she had to fly past her destination for a layover in Dubai, double back to Casablanca, and then take a three-and-a-half-hour drive to Tangier. What would have been a seven- to eight-hour direct flight was instead a nearly 24-hour odyssey. This is not unusual, she says.

The hassle of traveling within the region isn’t the only thing making things difficult for Africa’s research community: the difficulty of traveling out of the region has often left its researchers out of the international conversation. While these issues have affected every scientific field, they are amplified in AI research. The pace of innovation means, for example, that repeatedly missing conferences over visa problems—which have made it hard for African scientists to attend some of the world’s largest AI events in the US and Canada—can easily cause a researcher to fall behind.

Story from MIT Technology Review. Story by Karen Hao.

Despite the odds, the African machine-learning community has blossomed over the last few years. In 2013, a local group of industry practitioners and researchers began Data Science Africa, an annual workshop for sharing resources and ideas. In 2017, another group formed the organization Deep Learning Indaba, which now has chapters in 27 of the continent’s 54 countries. University courses and other educational programs dedicated to teaching machine learning have burgeoned in response to increasing demand.

The international community has also taken note. In late 2013, IBM Research opened its first African office in Nairobi; it added another in Johannesburg, South Africa, in 2016. Earlier this year Google opened a new AI lab in Accra, Ghana, and next year ICLR, a major AI research conference, will host its event in Addis Ababa, Ethiopia.

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The shift is a positive one for the field, which has suffered from a lack of diversity and, in many ways, a detachment from the real world. Many of the academic and corporate research labs that dominate AI research are concentrated in wealthy bubbles of innovation like Silicon Valley and China’s Zhongguancun, outside Beijing. That limited purview shows in the scope of the products these hubs create. Africa, on the other hand, might offer a context with which AI can return to its original promise: creating technology that tackles pressing global challenges like hunger, poverty, and disease.

“I think for anyone who’s looking for tough challenges,” says Wayua, “this is the place to be.”

Read more at MIT Technology Review.