At the World Economic Forum’s annual meeting at Davos in 2019, the Mastercard Center for Inclusive Growth and the Rockefeller Foundation announced a five-year, $50 million commitment to “unlock the power of data for good.” At the time, Dr. Rajiv Shah, Rockefeller’s president, compared the work of “bringing data science to social impact” to “the introduction of science to medicine 100 years ago.”
A year later, in January 2020, the two partners launched the data.org platform to help expand the field. The domain builds on the success of DATA.org, a fund launched in 2002 by a group of philanthropists including recording artist Bono, with the singular goal of lifting the lives of Africans though interventions in HIV/AIDS, trade and financial inequity. Now, data.org is a home for partnerships that help nonprofits gain the capacity to “harness the power of data insights and analytics” through training resources and open-source tools.
When they first announced data.org, the partners issued a $10 million Inclusive Growth and Recovery Challenge to tap the talents and expertise of people working to advance transformational change through data science, with the intention of crowdsourcing scalable and sustainable solutions to some of the world’s most pressing problems.
Fast-forward to January 2021. To its credit, the challenge stayed the course in the midst of a global pandemic, hitting every gate between submission and evaluation to announce its eight winners right on schedule.
Here are five key data points about the process and the first challenge recipients.
The challenge has two founding partners: the Mastercard Center for Inclusive Growth and the Rockefeller Foundation. The center is an independent subsidiary of Mastercard that works to apply the company’s full resources to the problems of sustainable and equitable economic growth. Expanding economic opportunity is also one of the Rockefeller Foundation’s four core commitments, along with ending energy poverty, promoting public health and advancing better global food systems.
Among the founding duo’s first moves was a $20 million investment in Datakind, a global nonprofit that used the funding to transfer 250 data science and AI projects to a platform-based model. Datakind now serves as one of the challenge’s technical partners, along with Benefits Data Trust and Community Solutions. Tableau Foundation, the nonprofit arm of the Tableau platform, was an investing partner.
The open crowdsourcing challenge captured the interest of a wide range of qualified applicants from around the world, including for-profit and not-for-profit organizations, governments and U.N. agencies, collaborations and individuals. Projects had to have a charitable purpose while accruing no private benefit.
More than 1,200 applications were received and evaluated on the same set of criteria: the capacity to be impactful, replicable, scalable, practical and groundbreaking in the application of data science for good.
14 expert judges
The challenge’s judges represented all walks of life, from science to philanthropy, government and academia. They collectively logged more than 2,000 hours of evaluation.
Judges included Raj Chetty, William A. Ackman, professor of economics at Harvard and director of Opportunity Insights; Bayo Adekanmbi, chief transformation officer for MTN Nigeria; Himanshu Nagpal, deputy director of financial services for the poor at the Bill and Melinda Gates Foundation; Vera Songwe, United Nations undersecretary general and executive secretary of the Economic Commission for Africa (ECA), and Bruno Sanchez, principal scientist at Microsoft’s Al for Earth.
Eight winning projects
The challenge sought out ideas on lifting low-wage workers, supporting grassroots entrepreneurs and attracting investments in underserved cities and towns—but was open to any and all ideas that advanced inclusive growth.
Eight proposals rose to the top, along with a wage theft project in Australia funded in collaboration with the Sydney-based Paul Ramsey Foundation.
Shamina Singh, president of the Mastercard Center for Inclusive Growth, said the global scope of the winners was completely intentional, but that replicability is key to finding global solutions to global problems. Winners will begin their work in 11 countries beyond Australia: Bangladesh, Denmark, Egypt, India, Indonesia, Mexico, Mozambique, Nigeria, Tanzania, Togo and the United States.
Two of the winning projects target gender equality. Solar Sister will help women in Nigeria and Tanzania use the data sciences to enter emerging clean energy markets, while Women’s World Banking will engage partners in Mexico, Nigeria and India to increase credit access for low-income female entrepreneurs.
Two touch the United States: Community Lattice, a partnership between Kansas State University’s Technical Assistance to Brownfields Program (KSU TAB) and Fifth Ward Community Redevelopment Corporation, will deliver a cost/risk analysis for public investments. And a pilot from the University of Chicago’s Center for Data and Computing will study the factors giving rise to a digital divide in sparsely connected areas of the city and use assessment tools to target interventions.
Winners run the gamut on tactics. In one instance, GiveDirectly and the Center for Effective Global Action at UC Berkeley will use machine-based learning to create targeted assessments that optimize the delivery of digital cash transfers. For a full list of winners, click here.
One global network
Kickstarting a global network was a lot to achieve during a global pandemic, but the partners now hope their evidence-based approach to development will play an integral role in rebuilding.
“A year ago, data.org was launched with the belief that the world’s most pressing challenges and the lives of vulnerable people could be improved with data-driven insights,” said Mike Forman, Vice Chairman of Mastercard.
As the world begins emerging from the pandemic, Forman believes the awardees’ innovations will help ensure that “economic growth is inclusive and sustainable for everyone,” and that the challenge’s global network of data scientists will be essential to building the field of data for good.