Can data make the world a better place? The Data Science for Social Impact Collaborative thinks so

Profile picture for user Jerry.bowles By Jerry Bowles February 4, 2019
Summary:
Mastercard and The Rockefeller Foundation are funding a new data-driven model for collaborative philanthropy to the tune of $50 million.
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More than just Big Data?

Big data’s image has taken a thrashing over the past couple of years. A series of avoidable disasters has made Facebook public enemy number one and several high-profile hacks and breaches have combined to take a toll on trust in the big tech industry.

Somewhat lost amidst the sound and fury is the fact that private-sector businesses have been creating and deploying data science capabilities for many years and have used data insights to create thousands of products and services that are better, cheaper and better tailored to real customer needs. They have done so without being overly obtrusive or violating privacy norms.

Imagine if organizations in the non-profit, civic, and public sectors had access to the same kind of resources to apply to many of the world’s most pressing problems? They could use applied data to make their work go farther, faster, and ultimately help more people.

That’s the idea behind The Data Science for Social Impact Collaborative, a new $50-million investment over five years, from The Rockefeller Foundation and the Mastercard Center for Inclusive Growth to build the field of data science for social impact through a transformational model for collaborative philanthropy. Said Dr. Rajiv J. Shah, President, The Rockefeller Foundation:

We know the power data science can have for social good because we've seen it in action. When mission-driven organizations have the right talent, tools, and knowledge, data science can generate real human impact: helping vulnerable families access public benefits; saving water and money during droughts, and saving time in resettling refugees – so they can find homes and jobs faster.

Added Michael Froman, vice chairman and president, strategic growth at Mastercard:

We believe the digital economy needs to work for everyone. If we can close the gap by providing the civic and social sectors with the tools, talent, and investments they need to apply data science effectively, then we have a shot at solving some of the greatest challenges of our time. We see a world where the infinite promise of technological innovation can deliver on our goal of inclusive growth.

The collaborative’s first investment will be $20-million in funding to DataKind, a global non-profit that connects data science talent with social organizations--harnessing the power of data science and AI in the service of humanity. Founded by Executive Director Jake Porway in 2011, the organization has chapters in New York, Singapore, Bangalore, London, San Francisco, and Washington, D.C.

DataKind, which describes itself as a multidisciplinary team built of coders and statisticians, community builders and partnership organizers, united by a common mission to use data in the service of humanity, has deployed expert volunteer data scientists and engineers from their network of over 30,000 to work on more than 250 projects around the world. Said Porway:

The grant will allow DataKind to transition from a project to a platform-based model, thereby, supporting more organizations on a set of high impact areas, such as community health and inclusive growth. We’re humbled and honored that these two groups are supporting our mission.

Using data for social impact examples

The Rockefeller Foundation pointed to three examples of the kind of positive social change it hopes the data science collaborative will inspire.

  • Better Refugee Placement in Switzerland: Data scientists from the Immigration Policy Lab at Stanford University and ETH Zurich used historical data on where refugees found jobs to build an algorithm that optimizes placement of incoming refugees. The teams are piloting the algorithm in Switzerland, guiding Swiss immigration officials to make more efficient placements. The foundation says this is a key example of quickly turning high-quality machine learning science into a useful product that improves decision-making and ultimately benefits people’s lives.
  • Saving Money and Water in Drought-Stricken California: Amid record droughts and ravaging wildfires, DataKind worked with Moulton Niguel Water District in southern California, where they brought together a team of data scientists – led by a senior engineer at Netflix and researchers from UCLA – to build an algorithm that can accurately predict water demand down to the city block. They used to ship in water tankers at massive cost to meet demand; so far this algorithm has saved the district over $25 million. It also helped make Moulton Niguel one of the only water agencies that actually thrived during California’s recent droughts.
  • Making Essential Benefits More Accessible: Millions of people need food, healthcare, and housing but are not enrolled in programs that could help meet these needs. Each year, Benefits Data Trust --a grantee of The Rockefeller Foundation through its Communities Thrive Challenge-- helps tens of thousands of people receive critical support using data, targeted outreach, policy change, and new technologies. Since its inception, BDT has submitted over 800,000 applications and secured over $7 billion in benefits and services that help individuals and families reach financial stability. The same tools that are under scrutiny for threatening privacy or spreading disinformation can also be used to pave a better path.

My take

The world is drowning in data and more than 2.5 quintillions of new data are produced every day, according to the Google Machine. Properly collected and harnessed, all this data, combined with rapidly advancing analytics capabilities and AI, has not only the potential to make a lot of global companies more efficient and prosperous but also to improve the lives of billions of people around the world. Governments and non-profits are actively looking for new ways to advance their efforts through applied data.

The goal is a noble one: By growing the data science capabilities of social and civic organizations the collaborative can help local leaders uncover new insights and trends from their data and build more programs that produce real positive change for the communities they serve.