Innovations in remote sensing, machine learning, and big data analytics allow for more accurate, frequent, and granular insights related to global poverty and inequality.
We are in the midst of what some have called “the fourth industrial revolution,” borne by a sea change in technologies to measure, store, and analyze human information. Satellites ply the sky, taking billions of images of Earth and its inhabitants; mobile phones, crowdsourcing tools, and social media apps generate trillions of bytes of relational data every day; machine learning (ML) algorithms predict everything from our writing styles to which households are most at risk for flooding; wireless sensors measure and report real-time traffic, air pollution, and the sound of trees being felled in protected rainforests.
At scale, these novel data sources offer a significant potential to benefit humankind. This is particularly true in low- and middle-income countries (LMICs), where public administrators and service providers lack access to high quality socio-economic information on the communities they serve due to logistical and financial constraints. Data-driven research and public policy applications lag far behind their potential to support these actors, both because of technical training and data infrastructure barriers and because of concerns around bias, privacy, and trust.
CEGA works to realize the potential of the Data Science for Development (DS4D) ecosystem by supporting social scientists, engineers, data scientists, regulators, and public administrators to shape institutions capable of leveraging new data and analytical approaches that can address poverty and inequality in LMICs. We do this by funding research studies, hosting annual conferences and workshops, supporting skills development, and compiling technical resources for interested researchers, policymakers, and practitioners. We help resource novel approaches to measuring socio-economic indicators and facilitate sustainable economic development — while also supporting research on the limitations and concerns surrounding this work.
How machine learning is democratizing access to global satellite imagery
Read the MOSAIKS research brief (English)Initiatives
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The Togo Data Lab (the Lab) helps to accelerate the Government of Togo's transformation into a leader of publicly-led data science innovation.
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Privacy enhancing technologies (PETs) can mitigate privacy vulnerabilities, enable new types of data, improve social welfare, and foster innovation.
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Driving innovative approaches to improve the targeting of social protection programs in LMICs.
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Geospatial Analysis for Development
Driving new analytical tools and methods for conducting geospatial analysis to fight poverty and improve lives
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