May 21, 2021

AI for Good: The Community of Problem Solvers Using AI in Tanzania

Meet Essa Mohamedali community manager of Tanzania AI Lab and project manager at Sahara Ventures.

Artificial intelligence (AI) presents striking opportunities for Africa and the African people to capitalize on the Fourth Industrial Revolution (4IR). AI, an intelligent machine that works and reacts like a human, has use cases in the continent’s most pressing sectors of health, finance, and agriculture. 

Expected to add trillions to global GDP, disruptive technologies like AI bring immense value to society, but improper use can undermine the benefits. An algorithm with an underlying bias or incorrect data can lead to discriminatory decision-making despite a programmer’s good intentions.

To deliver the promise of AI in Africa, whether that be increased productivity or access, tech ecosystems must create a strong foundation that goes beyond innovative solutions and includes spreading awareness and building capacity. A place where AI practitioners, enthusiasts, policymakers, and everyone in between can congregate. An AI community.  

In Tanzania, Tanzania AI Lab hopes to be that place as it aspires to  “Positively impact one percent of Africans in 10 years” by being the leading enabler for AI for Good and empowering Tanzanians with the potential of AI for the growth of themselves and the nation. 

I spoke with Essa Mohamedali, community manager of Tanzania AI Lab, about the state of AI in Tanzania, the impact of AI on Africa, and how he sees Tanzania AI Lab evolving over the next 3-5 years.


How did your journey lead you to create Tanzania AI Lab?

My name is Essa Mohamedali, and I am co-founder and community manager of Tanzania AI Lab. I grew up in Arusha, a smaller city in Tanzania, and came to Dar es Salaam in 2018 to study Computer Science at the University of Dar es Salaam (UDSM). 

I’ve always been passionate about technology and its application. What fascinates me is how you can apply it in creative ways to solve problems. When I came to Dar es Salaam, I got involved in the tech ecosystem. Here I learned about artificial intelligence from a meet-up and connecting with people active in the space.

At one of the events, I met Jumanne Rajabu, the CEO of Sahara Ventures, who shared a similar outlook on tech. He focused on its application. I decided to align myself with their work, joining Sahara Ventures as an intern, and later transitioned to project manager. 

Around that time, Sahara Ventures had released the Tanzania AI report, which covered the state of the ecosystem. One of the key insights from the report was AI activity was happening in the country, but it was siloed, which is expected because when experts and practitioners get into their work, they focus on the execution. 

Discussing the report with Jumanne, it began clear that we needed a community to bring together the AI ecosystem. So we put out a call to anyone who could hear.

What’s the state of AI in Tanzania? 

What comes to mind is a toddler learning how to walk, whereby they’re smarter than we think, learning is exponential, but there is still much growth to occur. Today, we are still able to count the AI-related startups we know of on both hands.

However, it’s difficult to properly gauge because not everyone in the field is talking about the work they’re doing. Some are so into their work, while others are intentionally not speaking because they see AI as a competitive advantage. 


The three focus areas of Tanzania AI Lab.

Awareness and advocacy:

We create content (blog posts and a podcast) and host general discussions to build awareness. At these events, we discuss why you should care about AI and how you can deploy AI in different sectors.  

Capacity Building:

Capacity building is done through online sessions and workshops facilitated by practitioners both locally and globally. The topics vary and are often based on the practitioner’s interest or experience. We also host boot camps, but due to  COVID, we have put a pause on in person events.

Applied Research:

Applied research focuses on identifying challenges faced by the grassroot and building working prototypes that address these challenges. Our most recent, and largest applied research project was

Impact starts with deploying solutions that help the people. Yes, we need to build awareness and skill sets, but what good is it if it’s not applied for good? The first two culminate in the technology’s positive application, but moving towards applied research is tricky when you don’t have the first two elements down. 

Thoughts on the impact of AI in Africa? 

The impact will purely depend on who decides to take it up, their purpose, and what they’ve been exposed to. 

When you watch documentaries like “The Frontline: In the Age of AI” and “The Social Dilemma” and see how countries are implementing the technology for control and corporates for profit, you wonder, is this the type of technology we want to get into more people’s hands? 

But at the same time, if we try and brush it under the rug, those who know about it will still have access to it. So it’s best that we make sure more people are aware, have the skills to use it, and emphasize the technology’s ethical use. 

In the context of Africa, AI isn’t an organized movement where big companies are leading the way. In most countries, the work is happening in startups and amongst a group of students. 

And in these cases, how are they going about testing, deployment, and implementation? It’s happening within their circles and exposure areas. And if their circle is made up of people similar to them and their exposure is limited, they’re not going to consider all the nuances.

So, the impact is dependent on who has access to the resources to make the technology and their level of understanding, exposure, and awareness. This will determine if the technology is going to be a saving grace or another Skynet from The Terminator. 

The best we can do is guide anyone interested in the technology to make sure they’re exposed and understand the consequences. This includes government institutions that create policies and private companies that create internal guidelines for the technology. Because at some point, we will need to decide who is accountable for the impact, good or bad, otherwise justice becomes a tricky conversation.

In summary, as much as we want to say tech is powerful and has exponential capabilities, tech is a tool. Maybe we’ve gone up from a butter knife to a chainsaw, a lot more powerful, but in its essence, it’s still a tool, and it will depend on who is creating it and using it. Are we giving it to a butcher, a chef, or a carpenter because the results that will come out of it will depend on who’s wielding the tool and their understanding of the area they’re trying to implement the technology. 

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Building a community?

One person:

Having one person show up to an event is enough. It’s easy for people to sign up, like on social media, and chat in a group. Having one person take a step and come because of their interest is enough. 

Yes, it stings, but don’t think about the 20 people that registered that didn’t come. Focus on that one person who did show up. That’s the people you can grow the community with. Countless research shows that only a small percentage of people in online and offline groups drive the community’s growth and engagement.

Redefining community:

It’s a community as long as there is some exchange of ideas, perspectives, and knowledge. Even if it’s just a WhatsApp group where people have a conversation once every two weeks, that’s a good start. Getting one or two people to share a perspective and bounce ideas off of each other is enough momentum to grow the community.

Finding your community:

Before I got involved in AI, I thought Tanzania didn’t have an AI ecosystem. But the moment I started talking about AI, I realized there were so many people ready to talk about AI. They may not have the technical skills yet, but they’re still ready to engage or learn. I’ve met real estate professionals, teachers, doctors, and agriculturists who are interested in AI.


We don’t need to overwhelm ourselves. You need a support system. Having a passionate partner is great if you can find one. Ideally, the active members of the community will be able to pitch in or help drive growth. These things happen organically, so continue to express the passion you have and give it time. Slowly but surely, things progress and grow on their own.  

Your vision for Tanzania AI Labs over the next 3-5 years?

Tanzania AI Lab is a community, and I don’t want to force what I want on the community. I want the community to grow organically and decide the direction we should go. My role is to collect perspectives from the various personas (practitioners, newbies, academics, government, and private companies). And bringing them together in a way that the people benefit.

My personal bias is towards applied research, where we can implement solutions that inform larger-scale implementations. There’s also the chance to have a physical lab one day with supercomputers, where the community can come and use them at subsidized rates. Or a research center that focuses on applied research or a content creation facility that focuses on awareness and advocacy. 

Maybe we’ll be all of these at one time. But again, I wouldn’t want to force any of this onto the community. The community is not mine; the community is the communities. 


Built In Africa. What does that mean to you?’

Multiple perspectives come to mind when I hear the phrase Built In Africa. Building solutions for Africans by Africans and building solutions for the globe that come from Africa. But to me, these statements are incomplete.

Built in Africa, sure, but then what? There’s something we should be building towards when we say Built In Africa. I envision something collaborative by the African people where we are no longer saying; you’re from Tanzania, Kenya, or South Africa. Or from East Africa or West Africa. Rather we’re seeing Africa as a whole and working together. 

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