The Artificial Intelligence Labour Gender Gap in Africa

The project mapped the gender composition of AI projects and companies originating in countries across Africa to capture the diversity struggles particular to AI start-ups, examine what those struggles exemplify in an African context and determine the mechanisms that can be put in place to curb them.

For this study, we defined African AI companies as companies that were: (i)building applications with machine learning and deep learning algorithms, (ii)located in Africa, (iii) operational at the time of data collection, and (iv)companies with at least 2 employees. We compiled our list by evaluating entries we acquired by accessing and analyzing open-access material, including news articles, websites, corporate documents, academic articles, NGO reports, expert submissions, and other public sources. A total of 160 companies were investigated across 21 countries.

The study identified sex disaggregation in terms of overall disaggregation, industry and position (managerial or otherwise). Gender was determined by cross-referencing employee pictures and names. Information on the above was gathered from three sources - the projects’ websites, the projects’ LinkedIn Profiles and the specific employees’ LinkedIn Profiles.

More information on the methodology can be found at www.cipit.org