Lowering barriers in participatory research for machine learning and health across Africa

Our Mission

SisonkeBiotik is an open and inclusive community of researchers, practitioners and enthusiasts at the intersection of Machine Learning and Healthcare working together to build capacity and drive forward grassroots research initiatives in Africa for Machine Learning and Healthcare.

The tragic past of colonialism has been devastating for Africa. This has resulted in a technological space that does not understand our names, our cultures, our places, our history.

SisonkeBiotik roughly translates to “together Biotik” in isiZulu. Sisonke means “together” and Biotik is a play on Biotic “Life” (both in terms of healthcare and people) and BioTech “biological technology”

Our goal is for Africans to shape and own these technological advances towards human dignity, well-being and equity, through inclusive community building, open participatory research and multidisciplinarity

Our Values

• Umuntu Ngumuntu Ngabantu - loosely translated from isiZulu means “a person is a person through another person” or “I am because you are”. This philosophy calls for collaboration and participation and community. It proposes relationality, over individualism for stronger social cohesions towards sustainable communities. It believes we share our successes and one’s personhood is evaluated based on their contributions to the community.

• African-centricity. We centralize the narratives of Africans as a remedy to the effects of Euro-centricism on our beliefs. This way we reassert a new way of looking at information from a African perspective and shun any attempts to devalue our knowledge and stories

• Ownership - We believe that Africans should be in charge of owning, driving and participating in the NLP research process, rather than as observers or data providers.

• Openness - We believe in sharing our ideas and progress openly, especially on the African continent, for Africans. We’re against research that takes African contributions or data and puts them behind a paywall that is infeasible for Africans to access.

• Multidisciplinarity - We truly believe that participation from all fields and experience and that multidisciplinarity leads to a more robust and more inclusive society

• Everyone has valuable knowledge - We believe that each person’s individual experiences have value and each person is worth listening too and has something to contribute.

• Kindness - We believe that being considerate, friendly and generous within our community is the best way to support it and encourage more inclusivity

• Responsibility - We believe that each person in the technology process has an ethical responsibility to what they produce in the world. For this reason, we actively wreckon with the ethical impacts of our work

• Data sovereignty - We believe Africans should be able to decide what data represents our communities globally, retain ultimate ownership of that data, and know how it is used

• Reproducibility - We believe in reproducible research. As a result, we publish our code and data from our research so that others can reproduce and build upon it.

• Sustainability - We believe that sustainability is necessary for societal change - that small daily efforts, over a long time are what truly change the world. To that, we aim for sustainability of our work, by being fully integrated with technological stakeholders to ensure the community continues to thrive into the future

Goals

• For Africa: To build and facilitate a community of Machine Learning and Healthcare researchers, connect and grow it, spurring and sharing further research, build helpful tools for applications in government, medicine, science and education, to enable language preservation and increase its global visibility and relevance.

• For Machine Learning and Healthcare Research: To help bridge the technical and social gap between Machine Learning and Healthcare. To increase accessibility of African health datasets, to help build African datasets, and to facilitate Machine Learning and Healthcare research in Africa. To pose new research problems to enrich the Machine Learning and Healthcare research landscape.

• For the global researchers community: To discover best practices for distributed research, to be applied by other emerging research communities.

How can I contribute?

There are many ways to contribute to SisonkeBiotik.

Generally

1. BRAINSTORM - Join our weekly meetings, provide advice or ideas

2. INTEREST GROUPS - Join a specific interest group on the SisonkeBiotik Discord Server

3. DOCUMENTATION - Help document our discussions and progress -This is VERY much needed

4. MENTORSHIP - Provide advice

5. ADMIN - Working with so many researchers can be quite a challenge! Help out with administrative tasks

6. COMPUTE - Help with infrastructure and compute! Do you have spare compute to donate? Let us know! We're always looking for more!

7. STORY-TELLING - Tell our stories to the world by doing talks about the community

8. MLOps & ML Engineering - Do you enjoy delving into the MLOps side of machine learning? Are you a software developer looking to hone-in on your ML engineer abilities? Join us to help build tools to support out reproducability, data gathering, and model sharing!

RESEARCH INITIATIVES

1. START RESEARCH INITIATIVE

2. CONTRIBUTE TO A RESEARCH INITIATIVE

• DATA - Help build or find datasets

• ANALYSIS - Contribute analysis of data/models. You do not need any technical experience for this! If you're a healthcare practitioner, we can pair you up with a Machine Learning practitioner and you can help contribute analysis

Want more details? Check out our current initiatives

Partner Communities & Organisations

Support from

SisonkeBiotik is a fork of the Masakahne research community model - find their repository here and fork your own community today =D

or fork the SisonkeBiotik community repository here