Tech At Bloomberg

Data for Good Exchange 2019 Preview: People Track

September 03, 2019

Data for Good Exchange 2019's "People" track looks at the use of data science to tackle Sustainable Development Goals (SDGs) related to poverty & hunger.

The Data for Good Exchange 2019 conference will take place on Sunday, September 15, 2019, at Bloomberg’s Global Headquarters in New York City. This year, the conference theme is “Data Science for the SDGs” or how data scientists, corporations, policymakers, and researchers can collaborate on data science projects that will move us toward achieving the UN’s Sustainable Development Goals (SDGs) by 2030. These 17 goals are structured around the five pillars of the 2030 Agenda for Sustainable Development – People, Peace, Prosperity, Planet and Partnership – which were adopted by all UN Member States at the historic UN Sustainable Development Summit in September 2015.

In this first of 4 articles previewing this year’s conference, we take a look at the panels, workshops and presentations in the conference’s People Track. The conference sessions in this track will tackle some or all of the following SDGs:

We are determined to end poverty and hunger, in all their forms and dimensions, and to ensure that all human beings can fulfil their potential in dignity and equality and in a healthy environment.


10-10:45 AM
Panel #1: From information to insight to impact: cross-sector approaches to data science for gender equality (SDG5 and beyond)

Gender equality is a broad and complex issue that is relevant to the vast majority of the SDGs, as well as the sole focus of Sustainable Development Goal 5. Ensuring greater gender equality will also help us make progress towards many of the other SDGs. Research and evidence show, for example, that women’s empowerment helps ensure progress on a wide range of other development outcomes including economic growth, health, nutrition, education, as well as environmental protection and peace and stability. Given the breadth of gender equality challenges – and the multiplier effects linked with increasing women’s empowerment – data science approaches aimed at improving gender equality must also be broad, cross-sector, and connect the local, national, and global levels.

This panel will look at how data science is helping to illuminate the system-level or macro picture for gender equality policies across 129 countries around the globe, with data from the 2019 SDG Gender Index. Panelists from Equal Measures 2030 (EM2030), UN Women, Data2X , and the Tableau Foundation will touch on different elements of the data value chain as it pertains to gender equality, from designing data collection to using data visualization for decision making and advocacy.

11:00 AM-12:00 PM
Paper Presentations, Session A

  • Using big data to support public space research (presented by Avigail Vantu and Kristen Day)
  • How data governance technologies can democratize data sharing (presented by Daniel Wu and Kelsey Finch)
  • Associating ridesourcing with road safety outcomes: Insights from Austin, Texas (presented by Eleftheria Kontou and Noreen McDonald)
  • A case study for the effectiveness of machine learning for reducing lead service line replacement costs in Flint, Michigan (presented by Jared Webb, Jacob Abernethy and Eric Schwartz)

12:15-1:00 PM
Data for Good Exchange Immersion Fellows’ Presentation: Love City Strong US Virgin Islands (USVI) & City of Houston, Texas

2:00-2:45 PM
Panel #2: Data for Good 2030: Creating Sustained Capacity

At last year’s Data for Good Exchange conference, DataKind ran the “Data for Good 2025” Workshop. This session encouraged people from multiple sectors to work together to determine which big challenges still existed for the Data for Good movement and attempted to chart a path toward a vision of Data for Good ten years out. Since then, they have received a lot of great thinking and return this year with a report back to the community and a call to action.

During this lively, interactive session moderated by The Rockefeller Foundation, panelists from DataKind, New America, the City of New York, and the UN Secretary-General’s High Level Panel on Digital Cooperation will propose a cohesive vision for Data for Good 2030. They’ll focus primarily on what it will take to not just create more Data for Good projects, but also to provide dramatic increases to data science and AI capacity in the space writ large. They’ll be tackling this conversation from the perspective of large NGOs, international organizations, foundations, and corporations, looking at what part each can all play in creating sustained capacity for data science and AI toward a better world.

3:00-4:00 PM
Workshop: Enabling Responsible Data Ecosystems to Use Data for Social Good

Earlier this year, the Mastercard Center for Inclusive Growth and The Rockefeller Foundation announced a $50M ‘Data Science for Social Impact’ collaborative to accelerate the use of data science by empowering non-profit, civic and government organizations with the tools, expertise and other capabilities they need to help solve the world’s most pressing challenges. Now working together with the Organisation for Economic Co-operation and Development (OECD) and others, this group is creating principles and practices to build data science capacity for those working on the front lines of social change.

Under the umbrella of the UN Sustainable Development Goals (SDGs), this workshop, which will be led by representatives from Mastercard, The Rockefeller Foundation and The Governance Lab (GovLab), will take participants through the design elements for enabling responsible data ecosystems to use data for social good. Participants will leave with an understanding of the unique roles various ecosystem actors play—data users, data suppliers, civil society, academics, and data scientists, among others—in driving the data-for-social-good process. Objectives will be accomplished against a backdrop of understanding the rights of individuals, responsibilities of ethical organizations, and best practices required for data-for-good enablement.

4:05 PM-4:50 PM
Paper Presentations, Session B

  • Knowledge mining (KnoMi) to bridge the evidence-to-policy gap (presented by Lauren Oldja, Or Castle, Amanda Pogue and Brian D’Alessandro)
  • How high-resolution satellite imagery and artificial intelligence can support the SDGs: A spotlight on SDG3 (presented by Matthew Hallas)
  • Helping federal agencies use AI for citizen good: Our journey to developing the AI playbook (presented by Justin Koufopoulos)
  • Using data science to facilitate civic action (presented by Eric Kingery, Q McCallum and Stephan Brown)