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.

Le genre m’a collé à la peau: Intérêt de l’analyse genre dans une recherche sur l’IA

Dans le huitième blog de la série Recherche sur l’IA et COVID : voyages vers l’égalité des genres et l’inclusion), Tidiane Ndoye explique comment ses expériences ont nourri sa passion pour les questions de genre dans le domaine de la santé et son rôle en tant qu’expert principal en matière de genre dans le projet de recherche AI4COVID, Utilisation de l’intelligence artificielle pour lutter contre le COVID-19 au Sénégal et au Mali.

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.

Are women programmed to think less and do more?

In the second blog post of the AI Research and COVID: Journeys to Gender Equality and Inclusion series, Meghan Malaatjie reflects on the gender norms she learned in childhood, her personal experiences with these norms, and the impact on her career, and aspirations to address gender inequalities as a public health professional.

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.