The AI Conference that brought brilliant minds together: AFRICAI Conference

Audacious Coder.
5 min readJul 3, 2023

June 12–14 was the highlight of my month. I had the opportunity to travel to the stunning hilly land of East Africa, Rwanda, for a conference like no other. AfricaAI is a conference about advancing responsible and open AI ecosystems in Africa. It was held at the convention center in Kigali and this event was an eye-opener to everything AI and was attended by data representatives from across Africa in various domains.

AfricAI Conference 2023


I sat in for many sessions including the commercialization of AI Healthcare Solutions by Villgro Africa incubator which is an impact investor supporting emerging healthcare businesses in Africa. The session facilitated discussions on researchers’ datasets and how they can be utilized by the public through open source and still be commercialized by the researchers to help sustain them. It was a really reflective thought and definitely curious to spark more discussions on how datasets can also sustain their developers while giving access to others to enable improvement and aid in research.

I was quite excited to jump on the session on AI for Climate Action in Africa where we brainstormed on challenges we would like to solve in context to climate in Africa and resources that we would need to enable us to solve the challenge we brainstormed. It was quite interesting and informative sitting next to researchers, business experts, and policymakers contributing to finding solutions. It enabled us to identify the importance of infrastructure in Africa to make these AI models successful in implementation.

Brainstorming Session

Ever heard of Lacuna Fund?

Lacuna Fund is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled datasets that address urgent problems in their communities.

I had to join in on the dataset presentations from which research grantees of Lacuna Fund showcased datasets they collected and labeled ready to apply machine learning. The datasets were themed under three domains such as agriculture, health, and language.

I will mention the datasets which you can check out to learn more.

Agriculture datasets

  1. Machine Learning Datasets for Crop Pest and Diseases Diagnosis: Crop Imagery and Spectrometry Data

Primary Institution: Makerere University

2. Helmet labeling crops

Primary Institution: University of Maryland

3. A decision-supporting tool for developing community-led land use plans

Primary Institution: University of Glasgow, University of Hohenheum,NOTTECH Company Limited

4. High-Accuracy Maize Plot Location and Yield Dataset in East Africa

Primary Institution: Zindi

5. Eyes on the Ground Image Data

Primary Institution: IFPRI

6. Sensor-Based Aquaponics Fish Pond Dataset: loT Fish Pond Monitoring Datasets

Primary Institution: University of Nigeria Nsukka

7. A New Rangeland and Pasture Management Open Dataset for Namibia

Primary Institution: Farm4Trade Namibia Trust

8. Mobile ELISA Syndromic Datasets to Enable Rapid Machine Learning Automation for Pen-Side Disease Diagnostics in Livestock

Primary Institution: Makerere University

9. Enhanced agriculture datasets for remote crop monitoring

Primary Institution: Pula Advisors Ag

10. A region-wide, multi-year set of crop field boundary labels for Sub-Saharan Africa

Primary Institution: Farmerline Ltd

11. Drone-based Agricultural Dataset for Crop Yield Estimation

Primary Institution: KaraAgro AI Foundation

Language Datasets

  1. IgboSynCorp: Dataset for Igbo Natural Language Processing Tasks

Primary Institution: University of Ibadan

2. Financial Inclusion Speech Dataset for Some Ghanaian Languages

Primary Institution: Ashesi University

3. NLP Text and Speech Datasets for Low-Resourced Languages in E Africa

Primary Institution: Makerere University Artificial Intelligence Lab

4. Multimodal Datasets for Bemba

Primary Institution: University of Zambia

5. Machine Translation Benchmark Dataset for Languages in the Horn of Africa

Primary Institution: Lesan AI UG

6. Masakhane MT: Decolonizing Scientific Writing for Africa

Primary Institution: Masakhane Consortium

7. Bayelemabaga Aligned Bambara French Corpus for Machine Translation

Primary Institution: Rochester Institute of Technology

8. Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis

Primary Institution: Bayero University ,Kano

9. Named Entity Recognition and Parts of Speech datasets for African languages

Primary Institution: Masakhane Consortium

10. KenCorpus: Kenyan Languages Corpus

Primary Institution: Maseno University

11. Igbo Dictionary API

Primary Institution: Nkowa Okwu

12. KALLAAMA — Speech Datasets for 5 Senegal Local Languages

Primary Institution: JOKALANTE

13. Naija Voice: Curation of speech-text corpora for ibo, hau, and yor

Primary Institution: Masakhane

14. Domain adaptation datasets for African languages

Primary Institution: University of Ibadan

15. Masakhane NLU: Conversational Al & Benchmark datasets for African languages

Primary Institution: Masakhane

16. Datasets marking Personal Identifiable Information (PI) and Gender Bias

Primary Institution: Makerere University Artificial Intelligence Lab

17. AfriHate: A Multilingual Hate and Offensive Corpus for Africa

Primary Institution: Bayero University, ICT4D Bahir Dar University (co-leads)

18. Development of Speech Corpora for Six Ethiopian Languages

Primary Institution: School of Information Science, College of Natural and Computational Sciences, Addis Ababa University

19. Building parallel corpora for Kenya’s Indigenous Languages and Swahili

Primary Institution: Maseno University, Kabarak University

20. Expanding a parallel corpus of Portuguese and the Bantu language Emakhuwa

Primary Institution: Lurio University

Health Datasets

  1. Reducing childhood malnutrition in Chile

Primary Institution: Universidad Adolfo Ibanez

2. Smartphone artificial intelligence platform for paper record digitization

Primary Institution: University of Virginia

3. Expanding BraTS Data to Capture African Populations (Africa-BraTS)

Primary Institution: Lawson Health Research Institute

4. ML from Real Patient Outcomes to Reduce Racial Disparities in Chronic Pain

Primary Institution: The University of Chicago

5. Datasets for Al-Based Diagnosis of Malaria

Primary Institution: Makerere University

6. National Chest X-ray Imaging Dataset for Multiple Cardiorespiratory Diseases in Ethiopia

Primary Institution: Addis Ababa University

7. Machine Learning-Ready Tuberculosis Chest X-ray Database for Africa

Primary Institution: Ernest Cook Ultrasound Research and Education Institute(ECUREI) , Mengo Hospital

8. Establishment of Machine Learning Datasets for Better Healthcare Outcomes

Primary Institution: Ifakara Health Institute

9. AI-assisted smartphone microscopy for automatic detection of parasites

Primary Institution: NepAI Applied Mathematics and Informatics Institute for Research (NAAMII)

  1. ACCELERATOR — Fair Clinical Machine Learning data training consortium

Primary Institution: Emory University School of Medicine

I was quite intrigued by the amazing work researchers are doing across Africa with the goal of using AI to benefit all and make society better by solving high-impact challenges facing the communities.

The datasets are published on various platforms such as MLhub, GitHub, Radiant Earth, hugging Face for language data, and many more. All you need to do is GOOGLE!! and ensure it's from the primary source mentioned.

Lastly, in collaboration with Zindi ( The largest professional network for data scientists in Africa), a challenge was introduced on Masakhane Parts of Speech Classification. If you are interested in getting your hands dirty, you can find the challenge here.


Apart from enjoying all these sessions I got to attend, my favorite highlight was interacting with the attendees I even got to meet Deshni Govender, who moderated a panel discussion for women in data that I was in during the covid 19 pandemic and we reconnected again in person. I also got to meet amazing people in data, especially in the Kenya ecosystem which was a delight!

Many thanks to the hosts and partners that enabled this event to happen and quite excited for the next conference !!

Signing out!

Audacious coder🙏



Audacious Coder.

Hyper-active Data Scientist | STEMINIST | Neuroscience Enthusiast | Dancer |Writer of DS/ML articles😄