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Pockets of excellence of people are breaking barriers at the frontier of AI even in Africa – Shingai

AI Education Director, ChainML, Shingai Manjengwa, collaborates with clients to navigate the realms of AI education, fostering adoption, and overseeing seamless implementation. Drawing upon her expertise, she guides clients from conceptualising AI product ideas to achieving cost-effective and scalable deployment. She shared her views on AI education and how it could change the world. She spoke with Elvis Boniface, publisher & CEO, Edugist at the just concluded World Innovation Summit for Education (WISE 11). Excerpts
Shingai-Manjengwa-Photo
Shingai Manjengwa. founder, The Fireside Analytics Inc. -Photo credit: Shingai
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We know what you do reviewing your profile. How did you get into AI in education?

I am a data scientist by profession and the first job I got out of the university was analysing point of sale data on behalf of retailers and manufacturers brands such as Johnson and Johnson, Colgate, and more were my clients. This introduced me to data services, architecture and computer programming starting with SQL.

How I got into education is an interesting story. I have been a data scientist and when I moved to Canada, in 2013. I had been studying and working in South Africa but when I moved to Canada, in 2013, I realised in the market that many people who knew about data science had never encountered a data scientist.

So, when I described which media is performing the best in terms of whatever content you would put out people would ask me, how did you know that? Data, course. It became increasingly apparent to me that people need to learn before they can leverage data and data science.

I started Fireside Analytics Inc. which was doing data science education and then the difference between data science and artificial intelligence (AI) is the modules. AI uses mirror method modules.

Fireside Analytics

We talk about different types but more specifically we get into reinforcement learning in addition to traditional machine learning. This is how I got into AI. I studied data science, did some work educating people to leverage AI and I joined an organisation that was doing AI education work.

How has this been?

It has been great. In the journey with Fireside Analytics Inc., my startup, I felt the limitation was me because I felt I could find experts to help me develop educational programming but students needed to understand the methods, tools and techniques. The speed with which I could produce content, I thought I was limiting myself.

When I joined the Vector Institute, in Canada, I had access to over 600 researchers who were working on everything and topics that no one person was an expert on but I could now access researchers working in these areas. This allows me to create content that is more diversified and sophisticated.

Read also: We found an alternate pedagogy that is experiential, learn by doing – Agustín Alejandro

The argument about the adoption of AI in education is often that those who code the algorithms are engineers, and scientists without necessarily working with educators. Do you agree?

This is a good point and think there is room for everyone. My journey as I mentioned was that I joined an analytics company out of the university. My undergraduate degree was in business, my majors were Politics, Philosophy and Economics.

I had to learn about technology on the job. I had to learn SQL from colleagues work it out, from the manual and test things. In this regard, nobody was talking to me about pedagogy, module one or module two. And I have a lot of empathy for people working under pressure because sometimes they don’t have the latitude of time to go into pedagogy.

This is why many of the online courses I ended up developing that have over half a million people that are taking them some in Nigeria, some in different parts of Africa, Asia and everywhere in the world resonate with many professionals because empathise with them. They explain topics using case studies that are relevant to work because I am a working professional.

Let’s talk about your courses and the numbers. Was that what you saw when you started?

Not. I could not have imagined it and today, just now, a lady from Jordan approached me and said ‘I was looking for you.’ She said ‘When I came to campus and saw your profile, I wanted to see.’ you. I have been following your work.

You can’t imagine that. I grew up in Zimbabwe, I lived in South Africa, and now I am in Canada, but I still see myself as the girl who grew up in Harare, to have people from all over the world come to say Shangai I have been following work or your courses have helped me change career paths. You cannot imagine that.

Zimbabwe, South Africa, and Canada, how do you see these realities about AI adoption in education? How do you benchmark Africa to Canada, for instance?

Let’s avoid generalisations because there are pockets of excellence of people breaking barriers at the frontier of AI even in Africa. I think it is also true that if you analyse the education system we can break it down into four functions – they have some administrative component, they have the teaching component, they have the learning and the students and then they have research.

If we can apply AI to the administrative process in Africa, oh my goodness, we could make such a difference. The process of a student getting into college, and the physical papers that we have to sometimes advance is an area that AI can advance in Africa.

In terms of how we deliver content, there is also an opportunity there because we have instances where the students are learning about titration and they have to learn the colour of potassium permanganate from a textbook, they look around and don’t know what is going on. But AI can make this learning available.

For the learners themselves, I think they must be exposed to AI because this is what we use on the job. In my profession I use code generation, code pilot, I use, text generation methods, ChatGPT and some of the other language models, I use image generation to make me better at my job. If we want to prepare African students for the future they must have access to tools and techniques.

Lastly, on research, we must leverage for research because a lot of research that we are using is based outside of our context. The diseases that we suffer and rely on other people to come and help us, but we are capable, we are intelligent. So the power of AI can change this.

The government still makes most of the decisions about AI. What would you recommend as a playbook for government and private sector organisations such as yours to meet?

I think everything, whether it is business, education or different causes, everything starts with leadership. If start with the leadership and political will to do the best for our children, and society this is a point of departure and a set of values to rally around. We just agree that we want to do well on one front, maybe it is job creation, and maybe it is entrepreneurship climate crisis or conflict resolution.

Whatever we prioritise then we bring the private sector in. We tell them this problem we are trying to solve, how can you help us? Can we keep doing what we are doing in Africa in terms of leadership and be successful or competitive? The world has changed.

What does this WISE 11 theme mean to you?

I love WISE, the premise for this conference. It brings together people to solve problems in education. We get together, talk about our issues and exchange ideas. It is even more important because the world has changed, our children are going to grow up in a different time.

Our grandchildren are going to ask what was like when ChaptGPT was launched. It is a new era in the use of these tools and techniques. The best part is that educators are open to learning, understanding and exploring leveraging technology in the classroom, to advance learning and education. I like this conference and it is outstanding how we can bring the right people together.

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