Gender Mainstreaming into African Artificial Intelligence Policies: Egypt, Rwanda and Mauritius as Case Studies

Abstract

Bias, particularly gender bias, is common in artificial intelligence (AI) systems, leading to harmful impacts that reinforce existing negative gender stereotypes and prejudices. Although gender mainstreaming is topical and fashionable in written discourse, it is yet to be thoroughly implemented in practice. While the clamour for AI regulation is commonplace globally, most government policies on the topic do not adequately account for gender inequities. Africa, Egypt, Rwanda and Mauritius are at the forefront of AI policy development. By exploring these three countries as case studies, employing a feminist approach and using the African Union Strategy for Gender Equality & Women’s Empowerment for 2018–2028 as a methodological guide, this study undertakes a comparative analysis of the gender considerations in their policy approaches to AI. It was found that a disconnect exists between gender equality/responsiveness and the AI strategies of these countries, showing that gender has yet to be mainstreamed into these policies. The study provides key recommendations that offer an opportunity for African countries to be innovative leaders in AI governance by developing even more robust policies compared with Western AI policies that fail to adequately address gender.

Keywords

• gender mainstreaming
• artificial intelligence
• african artificial intelligence policies
• ai governance
• gender and ai