Patrick Meier: Using Big Data to Inform Poverty Reduction Strategies — Data Science for Social Good: Not Cognitive Surplus but Cognitive Mismatch

01 Poverty, 03 Economy, 07 Health, 11 Society, Crowd-Sourcing, Geospatial
Patrick Meier
Patrick Meier

Using Big Data to Inform Poverty Reduction Strategies

My colleagues and I at QCRI are spearheading a new experimental Research and Development (R&D) project with the United Nations Development Program (UNDP) team in Cairo, Egypt. Colleagues at Harvard University, MIT and UC Berkeley have also joined the R&D efforts as full-fledged partners. The research question: can an analysis of Twitter traffic in Egypt tell us anything about changes in unemployment and poverty levels? This question was formulated with UNDP’s Cairo-based Team during several conversations I had with them in early 2013.

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Data Science for Social Good: Not Cognitive Surplus but Cognitive Mismatch

I’ve spent the past 12 months working with top notch data scientists at QCRI et al. The following may thus be biased: I think QCRI got it right. They strive to balance their commitment to positive social change with their primary mission of becoming a world class institute for advanced computing research. The two are not mutually exclusive. What it takes is a dedicated position, like the one created for me at QCRI. It is high time that other research institutes, academic programs and international computing conferences create comparable focal points to catalyze data science for social good.

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