Africa as an entire continent has been plagued with poverty and income inequality for many years now, there hasn’t been a lot of change of public opinion regarding this. However, there does seem to be a new wave of change coming to tackle this widespread disease. According to Reuters, 26-year-old South African computer scientist Raesetje Sefala found herself in the news for trying to tackle the problem through an AI tool.
1⃣ Local knowledge is power
⭕️ More Africans are drawing on their own lived experiences to design AI-driven solutions.
???? For developer Raesetje Sefala, this meant building algorithms flagging poverty hotspots – creating datasets she hopes will help target aid or housing. pic.twitter.com/wQQtUwsPBU
— Thomson Reuters Foundation (@TRF) February 18, 2022
AI, its Capability, And The Youth?
Raesetje Sefala has started building algorithms that will target ‘poverty hotspots’. These algorithms will help create ‘datasets’ that can narrow down the places that need help like new housing and clinics.
Sefala, is the first research AI fellow at the Distributed AI Research (DAIR) institute, which is a community-driven research group. She believes that if people with ‘diverse experiences’ are not included in the research, the data is at risk to be interpreted in a way that will marginalize other people. It is essential for local AI developers to be included so that applications can be developed keeping in mind the various local problems posing risks.
Africa has the world’s highest amount of youth population and according to tech experts, young candidates are the most suitable to be AI developers. Togo’s minister of digital economy and transformation, Cina Lawson said, “For Africa to get out of poverty, it will take innovation and this can be revolutionary because it’s Africans doing things for Africa on their own.”
She also added that it is essential to use the bleeding edge of technology to tackle such problems because obsolete methods of ’20 years ago’ will not do any good to solve problems in 2022.
The Reality of AI Prediction
Raesetje Sefala has mapped out all the townships and suburbs in South Africa and combined the tool of machine learning algorithms along with satellite data, merging it with the mapped-out dataset. Combining all of these, the growth of all these neighborhoods can be gleaned over time.
However, these algorithms were not free of caveats, the townships were not being predicted correctly. The algorithms could only be correctly predicted when lived and experienced data was applied.
Since AI is used in varied fields like logistical analysis to data science, it would be interesting to see where this burgeoning field takes us with the youngest continent in the world trying to make a useful difference.
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