Special Issue on Statistics and Data Science for Good

Special Issue on Statistics and Data Science for Good

One lesson that our team has taken from the past 18 months is that no individual, no team, and no organization can be successful on their own. We’ve been grateful and humbled to witness incredible collaboration—taking on forms of resource sharing, knowledge exchange, and reimagined outcomes. Some advances, like breakthrough medicine, have been widely publicized. Other advances have received less fanfare. All of these advances are in the public interest and demonstrate how collaborations can be done “for good.”

In reading this issue, we hope that you realize the power of diverse multidisciplinary collaboration; you recognize the positive social impact that statisticians, data scientists, and technologists can have; and you learn that this isn’t limited to companies with billions of dollars or teams of dozens of people. You, our reader, can get involved in similar positive social change.

This special edition of CHANCE focuses on using data and statistics for the public good and on highlighting collaborations and innovations that have been sparked by partnerships between pro bono institutions and social impact partners. We recognize that the “pro bono” or “for good” field is vast, and we welcome all actors working in the public interest into the big tent.

Through the focus of this edition, we hope to demonstrate how new or novel collaborations might spark meaningful and lasting positive change in communities, sectors, and industries. Anchored by work led through Statistics Without Borders and DataKind, this edition features reporting on projects that touch on many of the United Nations Sustainable Development Goals (SDGs).

Pro bono volunteerism is one way of democratizing access to high-skill, high-expense services that are often unattainable for social impact organizations. Statistics Without Borders (founded in 2008), DataKind (founded in 2012), and numerous other volunteer organizations began with this model in mind: If there was an organizing or galvanizing body that could coordinate the myriad requests for statistical, data science, machine learning, or data engineering help, there would be a ready supply of talented individuals who would want to volunteer to see those projects through. Or, put another way, “If you build it, they will come.”

Doing pro bono work requires more than positive intent. Plenty of well-meaning organizations and individuals charitably donate their time, their energy, their expertise, only to have an unintended adverse impact. To do work for good, ethics is an important part of the projects. In this issue, you’ll notice the writers’ attention to independent review boards (IRBs), respecting client and data privacy, discussing ethical considerations of methods used, and so on.

While no single publication can fully capture the great work of pro bono organizations working in “data for good,” we hope readers will be inspired to contribute to open source projects, solve problems in a new way, or even volunteer themselves for a future cohort of projects. We’re thrilled that this special edition represents programs, partners, and volunteers from around the world. You will learn about work that is truly representative of the SDGs, such as international health organizations’ work in Uganda, political justice organizations in Kenya, and conservationists in Madagascar, to name a few.

Several articles describe projects that are contextualized with the SDGs. While achieving many goals is interconnected, such as the intertwining of economic attainment and reducing poverty, we hope that calling out key themes here will whet your appetite for exploration.

We sincerely hope that you enjoy this issue highlighting the use of data and statistics in the public interest and how collaborations are vital to this process. We’re excited for this issue to inspire you to give back in some way, whether through Statistics Without Borders, DataKind, or another organization.

Caitlin Augustin is responsible for delivering DataKind’s core offerings, ensuring that high-quality, data science interventions are created in partnership with social sector leaders. Before DataKind, Augustin worked as a research scientist at a digital education company and as an engineering professor at New York University. A lifelong volunteer, she is engaged with Central Florida’s nonprofit community and the organizer of the Orlando Lady Developers Meetup. Augustin holds a BSIE and a PhD from the University of Miami.

Matt Brems is senior manager of data science product and strategy with DataRobot and managing partner and principal data scientist at BetaVector, a data science consultancy. His full-time professional data work spans computer vision, finance, education, consumer-packaged goods, and politics. He received General Assembly’s 2019 Distinguished Faculty Member of the Year award. He earned his master’s degree in statistics from Ohio State. Brems volunteers with Statistics Without Borders and currently serves on their Executive Committee as vice chair.

Davina P. Durgana is an award-winning international human rights statistician who has developed leading global models to assess risk and vulnerability to modern slavery. She is a report co-author and senior statistician of the Walk Free Foundation’s Global Slavery Index. She is the American Statistical Association’s 2016 Statistical Advocate of the Year, chair of Statistics Without Borders, and a 2017 Forbes Top 30 Under 30 in Science for her work in statistical modeling, human security theory, and human trafficking. She holds a PhD from American University.

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