Vukosi Marivate helped build societies and scientific networks for African researchers in machine learning and artificial intelligence (AI).Credit: Mariki Uitenweerde
During a PhD in the United States, the computer world discovered Fukusi Marfievity both the strength of the comprehensive spaces and the feeling of isolation resulting from the non -various gatherings. Since then, Marivate, who is now a data scientist at the University of Pretoria in South Africa, has been building a critical bloc of African data scientists – so that their voices can be part of the artificial intelligence revolution (AI).
In 2016, Marivate and his colleagues established the Deepa learning conference (BANTU languages, Cronic Important consultation or discussion (to help build a local community on machine learning and Amnesty International. The 2023 conference, which was held in Accra, Ghana, attracted 800 researchers from more than 62 countries, half of which are in Africa.
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Marivate also participated in the founding of Masakhane, a popular community of more than 1,000 researchers, software developers and language specialists from 30 African countries, which aims to avoid research in the treatment of natural language in African languages, for Africans and among them. Natural language processing uses machine learning techniques to process text and speech, for purposes such as translation and copying. Historically, 2000 languages in Africa have been neglected in digital products. One of the MACAKHANE projects has created scientific terms for African Languages, and the community continues to generate Africa -led groups and companies on the continent.
When did you realize that you want to address the lack of diversity in science?
During a doctorate at the University of Rutgers in New Bronzwick, New Jersey, I remember going to the International Methodological Conference, one of the best meetings in the world on this topic. I walked to a room full of people and on the other side of the giant hall was the only black person there. It spoils your mind and starts to ask, “What is happening here? Why are there only two of us?” You feel as if you do not belong.
For this reason, I need to make sure to open the doors to others. It is related to access. How do we make sure that people who are applying for international financing or fellowships better represent the African continent, and help them realize that they can be excellent, like anyone else?
I also learned that it does not necessarily need to be me who helps them: it is related to the use of the network, and the question of those working in these areas topics – in the same country or on the continent – then ask how I can connect students in those spaces. Deepaba and Masakhane are much larger than any individual networks.
Why does diversity, fairness and integration work?
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Once you start dealing with knowledge in a societal way, you see that people who are really pushing for innovation to enter their societies tend to be completely different from those who chase the highest levels of prestige of science.
I think the best is to come. Young people in the African continent will do more than us, and elderly scientists. They have better networks. They have more global recognition of the work they are doing. We will get amazing work from these young people and others who are not usually represented in these spaces.
What are the obstacles that Africans face in global artificial intelligence spaces and computing spaces?
The original model of the researcher of artificial intelligence tends to be a white male and from the global north. We try to say that your race, your disability, the type of sex and even your geographical area should not matter. We want people to feel comfortable, so that they can be themselves and bring themselves full to AI spaces and an account, without changing themselves to suit the system.
Other barriers include financing and pressure on students. For example, many South African students are likely to be in home and are often pushed towards non -research industry functions. How do we make sure that those who have a spark find places in discipline and have options?
Who was the biggest influence or teacher for you?
One is Tshilidzi Marwala, Amnesty International’s engineer in South Africa and President of the United Nations University in Tokyo. In 2006, I was studying engineering at Witwatersrand (Wits) in Johannesburg, and I wanted to work in a large engineering company and earn money. “There are more interesting things in the world that you may want to look at,” said Marwala. His laboratory was intelligent at the time, and there I saw people like me, and they have similar backgrounds to me. This experience changes you. He was also very generous with everyone, asking, “How do we open opportunities for you?” This was a major turning point in my scientific life.