Rediet Abebe uses algorithms and AI to improve access to opportunity for historically marginalized communities. When Abebe moved from her native Ethiopia to the United States to attend Harvard College, she was struck by how vital resources often fail to reach the most vulnerable people, even in the world’s wealthiest nation. She now uses computational techniques to mitigate socioeconomic inequalities.
While she was an intern at Microsoft, Abebe formulated an AI project that analyzes search queries to shed light on the unmet health information needs of people in Africa. Her study revealed such information as which demographic groups are likely to show interest in natural cures for HIV and which countries’ residents are especially concerned about HIV/AIDS stigma and discrimination. This work is the first to use large web-based data to study health across all 54 African nations.
She saw that resources weren’t reaching the people who needed them.
In an effort to inform health programming, Abebe is now taking these findings to health experts in ministries of health across the continent. She’s also working with the National Institutes of Health’s Advisory Committee to help reduce health disparities in the US.
To encourage growth in this area, she cofounded Mechanism Design for Social Good, a multi-institutional research initiative that uses algorithms to tackle problems ranging from allocating low-income housing to improving health outcomes.