This article reports a conversation that took place between SIID Fellow Dr Mike Smith, and Tẹjúmádé Àfọ̀njá.
Data Science Africa is a workshop and summer school that takes place each year in both East and West Africa. It began as a Gaussian Process summer school organised by the team in the AI Lab at Makerere, Uganda and Neil Lawrence’s lab in Sheffield, UK. Since then its broadened into a key networking event in the region. Tẹjúmádé Àfọ̀njá is an Engineering graduate, the organiser of AI Saturdays in Lagos and a participant in both of last year’s DSAs. I got in touch to get her take on the event and the role of data science in the region more generally.
Q: Data Science Africa involves a lot of committed people. You’ve become involved very quickly yourself. Can you describe how it’s organised and what your experiences have been? Who is it aimed at?
A: I first learnt about DSA bootcamp in 2018 through black-in-ai forum. It was themed – training for trainers: end to end data science. I was very excited and eager to apply because of the opportunities I felt such bootcamp could unlock. Prior to that, I had been organizing AI Saturdays Lagos classes (an Artificial Intelligence community where we go through curriculums from top-tier universities / MOOCs every saturday for 16 weeks) so I felt that this bootcamp could equip me with enough knowledge for me to share with my community back in Nigeria.
I’ve since attended two DSA bootcamps, one in Kenya and the other in my home country, Nigeria. Both bootcamps involved theoretical and practical sessions with leading AI researchers taking such sessions. My experience was surreal. Before my first bootcamp in Kenya, I was merely a machine learning enthusiast but the boot camp helped me answer some critical questions I needed to take the next step and fully seek a career in the field of Artificial Intelligence.
Hence, I believe DSA bootcamp is for anyone who is interested in the field of Artificial Intelligence.
Q: In recent years ARM has been helping to add an Internet of Things element to DSA. How did it go? What did you/they do? What does this add?
A: It was amazing and so much fun. We deployed several sensors like humidity and temperature sensors to monitor the Dedan Kimathi University of Technology greenhouse soil, air pollution LoRa sensors to monitor the air quality in nature reserve on campus,and a camera trap for species identification. Being able to see how we can combine IOT with data science was a brilliant idea, thanks to the organizers and ARM. Our projects solved real life problems and this is important for students to see and be able to think on how to apply these data science techniques on real world problems. In an ideal world, your chances of collecting a lot of data is usually through the use of sensors.
Q: There’s always time out from the presentations to chat over coffee and lunch. What conversations did you find most useful or inspiring?
A: I had a lot of inspiring conversations – so much that it’s difficult to pinpoint. One of such conversation was with Prof. Max Welling after his computer vision class where he took his time to re-explain the concept of backpropagation to me (because I just didn’t understand it at the time), I was blown away by his patience.
Q: What background did you have in data science and programming? And who do you think it would be most suitable for? Who do you think should attend?
A: I have a Mechanical Engineering degree, so I had very little background in data science and programming, I’m self-taught – thanks to the many freely available resources on the internet and inspiring colleagues doing amazing work thereby inspiring the rest of us to work a little harder and dream a little bigger. I think the bootcamp is for anyone/everyone. In fact, I’d argue that Data science is an essential skill set in the 21st century.
Q: People come from all over Africa and beyond to present. What did you find most interesting or applicable to your work?
A: Nyeri was my first trip outside my home country, and I’m very grateful for the opportunity it gave me to experience other people’s cultures and make new friends. I found the hospitality of people who were meeting me for the first time truly amazing. The trip filled my heart with more hope about humanity.
Q: DSA has been running now for five years, and last year was in West Africa too. Where do you think it’s heading? And do you have ideas for the future of DSA? How did you get involved with organising the event?
A: I think DSA bootcamps is definitely on to change the narrative of African AI researchers. A little more win every year and I’m excited to be a part of the journey. I hope this year, they’re able to get more sponsors to have more people attend the bootcamps. I can’t wait for this year’s bootcamps in Ethiopia and Ghana.
Q: So, given it’s been around for so long, what concrete benefits do you think now exist thanks to the event?
A: Thanks to DSA bootcamps, I’ve been able to connect with leading AI researchers who have been so kind to jump on a call with us despite their very busy schedule during our meetup sessions at AI Saturdays Lagos. I’ve also been privileged to have amazing people like Sara Hooker, Timnit Gebru, Prof. Neil Lawrence and so many more, providing me with advice and sending opportunities my way. These are connections and relationships which have been built at no cost other than being privileged to be amongst the boot camp students. I’d say there are unquantifiable benefits to events like this and we can’t simply thank the people that make such events possible enough.
Q: Maybe related to the above; What are your thoughts more generally about Data Science in Africa? Why’s it necessary or what are the problems?
A: I think it’s inevitable. Data is everywhere and this leaves us with questions like “what do we do with these data?”, whilst the rest of the world seem to have figured out answer(s) to this sort of question, Africa is slowly catching up. I believe the field of data science is paramount in the development of African economies. Data Science and Machine Learning promise a lot of solutions to our past and current problems. Companies can apply these tools to improve their products; government officials, likewise, can deploy these tools to some (if not all) aspect of their government. In governance, corruption can be drastically reduced, accountability might even be ensured and so on. In the educational sector, we can use these tools to better understand how each student is learning and the kind of materials to expose each learner to. In the health industry, the tools can be used to make quicker diagnosis of certain diseases. In the agricultural space, these tools can be used to help farmers understand the state of their yields and better plan for a farming season. There is so much we can achieve with the help of data science and machine learning; and the opportunities, as well as applications, are endless. However, we should also be aware of potential problems we are likely to encounter. Problems like efficient data collection process, bias & fairness, threat of unemployment, government policies, data science and machine learning talent shortages, lack of capital/resources needed to embark on projects and so on. The good news is that companies / individuals / the world is coming to realize the potentials Africa has to offer, thereby driving a lot of initiatives. Some of these initiatives include investing funds in Artificial Intelligence research / companies / organizations / communities, driving conversations around data policies, bias etc It’s an exciting time we live in and it’s our responsibility to make the world a little better than we met it with the use of AI. The future of Artificial Intelligence in Africa looks very bright!