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Innovations in remote sensing, machine learning, and big data analytics allow for more accurate (and frequent) insights related to global poverty

CEGA Work Theme - Data Science for Development

Motivation

The world is undergoing a data revolution–Satellites ply the sky, mapping our planet’s surface in real-time; mobile phones, crowdsourcing tools, and social media apps generate billions of data points every day. The potential for leveraging these data at massive scale for social good, and for public policy, is seemingly boundless, particularly in low- and middle-income countries (LMICs), where traditional data (like household survey data) is often expensive and hard to collect. However, data-driven research lags far behind potential, in part because of technical training and data infrastructure barriers, and in part because of justified concerns around bias, privacy, and trust.

CEGA is working to realize the potential of the “Data Science for Development (DS4D)” ecosystem by supporting social scientists, engineers, and data scientists to leverage new types of data and analytical approaches in addressing challenges related to poverty in LMICs. We do this by hosting annual conferences and workshops, supporting skills development, and compiling resources for interested researchers, policymakers and practitioners. We target novel approaches to measuring poverty and facilitating sustainable economic development — while also supporting research on the limitations and concerns surrounding this work.

Examples

CEGA has supported transformative research that leverages innovative data science approaches across a number of sectors:

Driving Impact

CEGA is committed to driving the adoption of cutting-edge methods and data, and the development of relevant public resources, in addition to developing and testing new DS4D tools and approaches. We’re doing this through partnerships with a wide range of stakeholders, including global technology companies, telecommunications companies, satellite companies, and innovation-minded research and policy partners. If you are interested in partnering with CEGA to develop, test, or train stakeholders on new DS4D approaches, please contact Sam Fishman sfishman@berkeley.edu.

 

Partners

United States Agency for International Development

GiveWell

GiveDirectly

Google.org

Pulte Institute for Global Development

Institute of International Studies

Development Impact Evaluation (DIME), World Bank Group

Development Economics Data Group (DECDG), World Bank Group

New Light Technologies (NLT)

Atlas AI

Data.org

Scientific Directors

Initiatives

Geospatial Analysis for Development

The Geo4Dev initiative is a collaboration between CEGA, New Light Technologies Inc., and 3IE building a hub for rigorous academic research and training that exploits geospatial data for the targeting, design, and evaluation of social and economic development programs. The initiative drives the development of new analytical tools and methods for conducting geospatial analysis across diverse sectors related to poverty and development including agriculture and food security, urbanization, climate change, humanitarian crisis, and disaster relief. Visit the Geo4.dev website and explore our curated...

Data Science for Development Research

Data Science for DevelopmentTechnologyWork & Education

Using High-Resolution Satellite Data to Evaluate The Impact of New Business


Gordon Hanson | India
Data Science for Development

Detecting Social Networks with Satellite Imagery


Jeremy Magruder | Malawi
Global NetworksData Science for DevelopmentHealth & Psychology

Remote Sensing and Estimation of Household Welfare in South Sudan


Reajul Chowdhury | South Sudan
Data Science for DevelopmentTechnology

High Resolution Development Indicators


Joshua Blumenstock | Afghanistan
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Data Science for Development Resources

Data Science for DevelopmentTechnology

(Machine) Learning What Governments Value


Working Paper   |   Technology
Data Science for DevelopmentFinancial InclusionTechnologyWork & Education

Targeting Development Aid with Machine Learning and Mobile Phone Data


Working Paper   |   Financial Inclusion
Health & Psychology

Video: "Diagnosing bias with machine learning" - Ziad Obermeyer (E2A 2019)


Presentations   |   Health & Psychology
Data Science for DevelopmentFinancial InclusionTechnology

Video: Josh Blumenstock | Targeting Anti-Poverty Programs Using Mobile Phone Data


Presentations   |   Financial Inclusion
Data Science for DevelopmentTechnology

Video: Josh Blumenstock | Fighting Poverty with Data


Presentations   |   Technology
Data Science for DevelopmentTechnology

Video: Keynote Address - Joshua Blumenstock | MeasureDev2020


Presentations   |   Technology
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News

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