Briefing Papers

Incorporating gender and intersectionality in Artificial Intelligence (AI) models and algorithms

Data, Measurement and Evaluation

Risks of harm from the multiple and overlapping crises related to COVID-19 vary based upon one’s gender, age (children, adolescents and elderly), level of education, occupation, geographical location (urban, rural, informal settlements, urban slums, camps), marital status (married, single, widowed), ethnicity/race, economic status, religion, disability (physical mobility, albinism, hearing disability).

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CONTRIBUTORS

Post-doctoral Research Fellow

Anne Khisa

Anne is the Program Coordinator for the UKRI-GCRF Accelerating Achievement…

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Associate Research Scientist

Sylvia Kiwuwa Muyingo

Sylvia holds a PhD in Biometry from the University of…

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Communications Officer

Michelle Mbuthia

Michelle is a Communications Officer in the Policy Engagement and…

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