Our Reflections

At Gender at Work, we are committed to reflection as both a political and pedagogical act, using it to reveal insights, challenge assumptions, and adapt our practices. Our approach to learning is emergent: shaped by context, grounded in feminist values and open to the unknown. We see learning as both a method and a muscle: something strengthened through practice, vulnerability and shared reflection.

Misconceptions and divides: my previous experience with GEI integration in research

In this first blog in the “Keeping the light on: Reflections on GEI and AI in Africa” series, Daisy Salifu, a biostatistician at the International Centre of Insect Physiology and Ecology (icipe) Data Management, Modelling and Geo-information unit, reflects on her own “aha moments” finding meaning and relevance of GEI in her own AI work in the agriculture and food systems field, implementing inclusion-by-design with women farmers and people living with disabilities in Uganda and Nigeria.

Meeting the world, the work, and colleagues in new ways: Working emergently in sustaining an online learning community

In early 2020, Gender at Work (G@W) was invited by the Human Sciences Research Council (HSRC), to partner in a project to support science granting councils (SGCs) across the African continent, to advance gender transformation in relation to science, technology and innovation (STI).

Cook, Clean, Plan: A case for more gender-responsive policymaking

In the third blog post of the AI Research and COVID: Journeys to Gender Equality and Inclusion series, Michelle Mbuthia discusses her personal experience of gender inequality and unfair distribution of domestic labor during the Christmas season in Kenya, and the need for candid discussions and collective efforts to challenge and change traditional gender norms and create a more equal society.

Can AI Have Its Cake and Eat It? Reducing Bias in AI Models May Not Always Be Desirable

In the first blog in the AI Research and COVID: Journeys to Gender Equality and Inclusion series, Amelia Taylor, a Senior Lecturer in AI at the Malawi University of Business and Applied Sciences and researcher with the INSPIRE PEACH project under AI4COVID, raises the ethical dilemmas of trying to create unbiased and representative algorithms of women and men impacted by epidemics.