The Next Chapter in Using Data Science & AI in the Service of Humanity

Dear DataKinders,


This is a big moment. You’ve been with us from the start because you believed that we had the opportunity to redefine how data science is used in pursuit of humanity’s greatest values. You pitched in your time, your efforts, and your support to make that happen. You believed that, one day, we might have a chance to actually shift the conversation around data and technology from helping make profits to helping support people.


We’re excited to say that we’re one big step closer to that goal.


Last fall, supported by The Rockefeller Foundation, we took a step back to reflect and reimagine our strategy and develop a long-term plan. It’s with total gratitude and excitement that I write to tell you that we have amazing news: we’re receiving $20M of funding to pursue the next phase of DataKind from the new Data Science for Social Impact collaborative established by The Rockefeller Foundation and the Mastercard Impact Fund – administered by the Mastercard Center for Inclusive Growth.


In this next chapter, we’ll be taking our work one step further by transitioning to support a thriving data science for good ecosystem writ large. In our grand vision, we see a world where all those who fight on the frontlines of social change can get solutions for their data science problems. Right now, however, too many organizations still can’t get access to the funding, talent, skills, or training to make that happen easily. This problem also can’t be solved solely on the backs of thousands of volunteers, but it can happen if we can help bridge the gaps between those who have data science resources to give and those who can use them. We believe we can make a dramatic shift in the social sector in the next five years by focusing our pro bono projects in key issue areas, learning about the common needs therein, and then using those findings and results to help connect data science resources (from foundations, technology companies, pro bono sources) to the data science needs (cohorts of social organizations, governments, and others who could use them). The end result of this work is that anyone who holds a “data science-able” social problem is able to ethically apply, create, or commission a data solution for it.


There will be more information coming out this year on the activities we have planned and what issue areas we’ll focus on. However, what I really want to touch on is how we’ll be doing this work. Let’s face it, we’re living through an age where people are rightfully skeptical of the applications of technology and data. International development is a sensitive field, and history is littered with examples of people trying to do good “to others”, all to fateful ends. Books like Winners Take All are popular because people are becoming increasingly aware of the inequity in the world and the many efforts of the powerful to use philanthropy for face-saving over real impact.


DataKind has long been an organization defined by the values of our community and the attitudes we keep, and we believe that how we do our work is often even more important than what we do. To that end, we’ll be working to uphold the following principles in this next phase:


  • Focusing on Issue Areas is Key to Learning Rapidly: We’ll be focusing our project work in key issue areas, where we find common solutions that could apply to many organizations at once. These could include issue areas like Community Health Work or common data science needs, like auto-summarization of research with natural language processing techniques. We’re going to opportunistically seek the areas with the most overlap, so we can learn quickly and make a greater impact for multiple organizations.
  • Being a Data Science for Social Good Ecosystem Builder Is a Support Role: We know the work of our global network of pro bono data scientists can play a hugely catalytic role in helping social change organizations experience the power of machine learning and data science in their own work. However, we’re not here to impose on organizations or insist on our practices being used in particular places. International development has a long history of individual organizations with grant money insisting that things be done “their way” without a needed respect for those on the ground who may understand the situation better. At DataKind, our first core value is humility, and we’re here to be supportive, to share our best practices, to connect where possible, and to only be a support where invited in. We’ll spend our first year working with partners to identify where we can be most helpful on their terms, not ours.
  • Scaling Ourselves Through Others: To reach our mission of empowering all to use data science for good, we must equip more people with the ability to use this technology well. We can’t be the sole provider of these services, and wouldn’t want to use this funding to grow in that way. Instead, we’ll use this support to share our best practices, create training materials, expand our chapter network, and disseminate more of the DataKind practice to the universities, technology companies, communities, and individuals who would like to take it and make it their own. Success for us means seeing a world where all can build off DataKind’s work and make it even better without us.
  • Ensuring “Data for Good” Means Data for All: Our vision of data science being used ethically and capably for all humanity means that it must be in the hands of all humanity. That means the only way to succeed in our mission is to see local leaders rise in their own communities. We can’t approach this work without an equity lens. If, in five years from now, we’ve created many projects, but have only supported communities of a certain dominant identity, or who already have the resources and means to ask for data science support, or those who are already in our DataKind network, we will have failed. We’ll simply have perpetuated the same systems of power that have created divisions and inequity in our world that we seek to address. No one group can solve for the varied needs of our global community, not without investing in and working alongside a diverse group of communities, including those often underrepresented in these conversations. We will therefore be spending time in our first phase listening to the people on the frontlines of social change voice their communities’ needs, and understanding if and where we can support the work they do. We’re committed to fostering a board, advisory council, staff, chapter leadership, and volunteer community that’s as diverse and inclusive as the world we hope to see, and we’ll be seeking support and learning on the best ways to do so. Although diversity has been a core value of DataKind’s since its inception, there’s so much more work for us to do in ensuring that we’re supporting our mission in the most equitable and inclusive ways possible. To that end, we look forward to being guided by and collaborating with individuals who can support these efforts further.
  • Learning Out Loud With You: The last principle we’re adhering to is that we must learn out loud for this experiment to work. The vision we seek requires a shift in culture, thinking, and best practices around how data science is used for the greater good. As a result, we’ll be sharing as much as is possible about how we make the decisions we make, why we partner with who we partner with, what worked well, what we failed at and why, and how we’re making progress toward our goals. We’ll be transparent about our funding decisions. We spent a great deal of time getting to know The Rockefeller Foundation and the Mastercard Center for Inclusive Growth to understand their core values before entering this partnership, and we were impressed to see their commitment to a more data-driven social sector. We invite you to hold us accountable to being louder about our hard learnings than our easy wins and encourage you, as a fellow member of the data science for good community, to join that journey with us.


We have a lot of work to do on all of these fronts, but we welcome your support in this exciting new phase, as it will take all of us to live these.


Thank you, from the bottom of my heart, for helping us get here. Whether you’ve been with DataKind from the start or just joined us now, it’s your commitment to a world in which data science is used for our greatest human needs that we’re at this exciting point. Now the real work begins, and we look forward to working alongside you toward a vision of a world where data science and AI are truly used, first and foremost, in the service of humanity.


To great things to come,

Jake Porway
Founder & Executive Director

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