Un marco para avanzar en la equidad de datos en un mundo digital
La equidad de datos es una responsabilidad compartida que requiere una acción colectiva para impulsar sistemas de datos justos y equitativos. He aquí por qué.
Lauren Woodman has spent 25 years working at the intersection of technology, development, and policy. Most recently, she was the CEO of NetHope, a consortium of 60 of the largest global nonprofits and tech companies from 2014-2020.
Before that, she held a variety of positions in the private sector, government, and the UN, including managing Microsoft’s global education and government programs for more than a decade and serving as an executive at the Software and Information Industry Association. Currently, she is a member of the World Economic Forum’s Board of Stewards for its Initiative on Digital Economy and its Trustworthy Data Collaboration. Lauren holds degrees from the Johns Hopkins School of Advanced International Studies and Smith College. She lives in Seattle with her partner and two daughters.
Lauren’s entire career has been defined by the intersection of tech, development and policy, driven by a passion to use technology to solve difficult international problems. With a graduate degree in foreign policy from John Hopkins School of Advanced International Studies, Lauren has worked in a variety of high-level positions: in policy at the United Nations, as an executive at the Software and Information Industry Association, and, for more than a decade, running Microsoft Corporation’s global education and government programs, all leading her to her leadership role at NetHope in 2014.
La equidad de datos es una responsabilidad compartida que requiere una acción colectiva para impulsar sistemas de datos justos y equitativos. He aquí por qué.
Data equity is a shared responsibility that needs collective action to advance data systems that promote fair and just outcomes for everyone. Here's why.
医疗保健领域的历史算法偏见揭示了数据公平的迫切需求。一项研究发现,纠正医疗保健中的种族偏见可以将接受额外护理的黑人患者的比例从17.7%提高到46.5%。
El sesgo racial en los algoritmos de atención médica expone problemas más amplios en los sistemas de datos en todos los sectores. La equidad de datos puede lograr resultados más justos.
Racial bias in healthcare algorithms exposes broader issues in data systems. Learn how the concept of data equity can lead to fairer outcomes across industries.
Discover why, in a world that increasingly relies on technology, trusted technical design is fundamental, and that trust must begin with full data equity.
Ahead of Davos, leaders from Habitat for Humanity, DataKind, Reporters Without Borders and the World Resources Institute share their thoughts on civic participation.
All of us involved in humanitarian and disaster-recovery work know that sharing information is a good thing. But there are many barriers that stand in the way and prevent the improved res...